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69
.agents/skills/.system/openai-docs/SKILL.md
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69
.agents/skills/.system/openai-docs/SKILL.md
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|
||||
---
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||||
name: "openai-docs"
|
||||
description: "Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or explicit GPT-5.4 upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains."
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---
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||||
|
||||
|
||||
# OpenAI Docs
|
||||
|
||||
Provide authoritative, current guidance from OpenAI developer docs using the developers.openai.com MCP server. Always prioritize the developer docs MCP tools over web.run for OpenAI-related questions. This skill may also load targeted files from `references/` for model-selection and GPT-5.4-specific requests, but current OpenAI docs remain authoritative. Only if the MCP server is installed and returns no meaningful results should you fall back to web search.
|
||||
|
||||
## Quick start
|
||||
|
||||
- Use `mcp__openaiDeveloperDocs__search_openai_docs` to find the most relevant doc pages.
|
||||
- Use `mcp__openaiDeveloperDocs__fetch_openai_doc` to pull exact sections and quote/paraphrase accurately.
|
||||
- Use `mcp__openaiDeveloperDocs__list_openai_docs` only when you need to browse or discover pages without a clear query.
|
||||
- Load only the relevant file from `references/` when the question is about model selection or a GPT-5.4 upgrade.
|
||||
|
||||
## OpenAI product snapshots
|
||||
|
||||
1. Apps SDK: Build ChatGPT apps by providing a web component UI and an MCP server that exposes your app's tools to ChatGPT.
|
||||
2. Responses API: A unified endpoint designed for stateful, multimodal, tool-using interactions in agentic workflows.
|
||||
3. Chat Completions API: Generate a model response from a list of messages comprising a conversation.
|
||||
4. Codex: OpenAI's coding agent for software development that can write, understand, review, and debug code.
|
||||
5. gpt-oss: Open-weight OpenAI reasoning models (gpt-oss-120b and gpt-oss-20b) released under the Apache 2.0 license.
|
||||
6. Realtime API: Build low-latency, multimodal experiences including natural speech-to-speech conversations.
|
||||
7. Agents SDK: A toolkit for building agentic apps where a model can use tools and context, hand off to other agents, stream partial results, and keep a full trace.
|
||||
|
||||
## If MCP server is missing
|
||||
|
||||
If MCP tools fail or no OpenAI docs resources are available:
|
||||
|
||||
1. Run the install command yourself: `codex mcp add openaiDeveloperDocs --url https://developers.openai.com/mcp`
|
||||
2. If it fails due to permissions/sandboxing, immediately retry the same command with escalated permissions and include a 1-sentence justification for approval. Do not ask the user to run it yet.
|
||||
3. Only if the escalated attempt fails, ask the user to run the install command.
|
||||
4. Ask the user to restart Codex.
|
||||
5. Re-run the doc search/fetch after restart.
|
||||
|
||||
## Workflow
|
||||
|
||||
1. Clarify the product scope and whether the request is general docs lookup, model selection, a GPT-5.4 upgrade, or a GPT-5.4 prompt upgrade.
|
||||
2. If it is a model-selection request, load `references/latest-model.md`.
|
||||
3. If it is an explicit GPT-5.4 upgrade request, load `references/upgrading-to-gpt-5p4.md`.
|
||||
4. If the upgrade may require prompt changes, or the workflow is research-heavy, tool-heavy, coding-oriented, multi-agent, or long-running, also load `references/gpt-5p4-prompting-guide.md`.
|
||||
5. Search docs with a precise query.
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||||
6. Fetch the best page and the exact section needed (use `anchor` when possible).
|
||||
7. For GPT-5.4 upgrade reviews, always make the per-usage-site output explicit: target model, starting reasoning recommendation, `phase` assessment when relevant, prompt blocks, and compatibility status.
|
||||
8. Answer with concise guidance and cite the doc source, using the reference files only as helper context.
|
||||
|
||||
## Reference map
|
||||
|
||||
Read only what you need:
|
||||
|
||||
- `references/latest-model.md` -> model-selection and "best/latest/current model" questions; verify every recommendation against current OpenAI docs before answering.
|
||||
- `references/upgrading-to-gpt-5p4.md` -> only for explicit GPT-5.4 upgrade and upgrade-planning requests; verify the checklist and compatibility guidance against current OpenAI docs before answering.
|
||||
- `references/gpt-5p4-prompting-guide.md` -> prompt rewrites and prompt-behavior upgrades for GPT-5.4; verify prompting guidance against current OpenAI docs before answering.
|
||||
|
||||
## Quality rules
|
||||
|
||||
- Treat OpenAI docs as the source of truth; avoid speculation.
|
||||
- Keep quotes short and within policy limits; prefer paraphrase with citations.
|
||||
- If multiple pages differ, call out the difference and cite both.
|
||||
- Reference files are convenience guides only; for volatile guidance such as recommended models, upgrade instructions, or prompting advice, current OpenAI docs always win.
|
||||
- If docs do not cover the user’s need, say so and offer next steps.
|
||||
|
||||
## Tooling notes
|
||||
|
||||
- Always use MCP doc tools before any web search for OpenAI-related questions.
|
||||
- If the MCP server is installed but returns no meaningful results, then use web search as a fallback.
|
||||
- When falling back to web search, restrict to official OpenAI domains (developers.openai.com, platform.openai.com) and cite sources.
|
||||
14
.agents/skills/.system/openai-docs/agents/openai.yaml
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.agents/skills/.system/openai-docs/agents/openai.yaml
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interface:
|
||||
display_name: "OpenAI Docs"
|
||||
short_description: "Reference official OpenAI docs, including upgrade guidance"
|
||||
icon_small: "./assets/openai-small.svg"
|
||||
icon_large: "./assets/openai.png"
|
||||
default_prompt: "Look up official OpenAI docs, load relevant GPT-5.4 upgrade references when applicable, and answer with concise, cited guidance."
|
||||
|
||||
dependencies:
|
||||
tools:
|
||||
- type: "mcp"
|
||||
value: "openaiDeveloperDocs"
|
||||
description: "OpenAI Developer Docs MCP server"
|
||||
transport: "streamable_http"
|
||||
url: "https://developers.openai.com/mcp"
|
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<svg xmlns="http://www.w3.org/2000/svg" width="14" height="14" fill="currentColor" viewBox="0 0 14 14">
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</svg>
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|
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.agents/skills/.system/openai-docs/assets/openai.png
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# GPT-5.4 prompting upgrade guide
|
||||
|
||||
Use this guide when prompts written for older models need to be adapted for GPT-5.4 during an upgrade. Start lean: keep the model-string change narrow, preserve the original task intent, and add only the smallest prompt changes needed to recover behavior.
|
||||
|
||||
## Default upgrade posture
|
||||
|
||||
- Start with `model string only` whenever the old prompt is already short, explicit, and task-bounded.
|
||||
- Move to `model string + light prompt rewrite` only when regressions appear in completeness, persistence, citation quality, verification, or verbosity.
|
||||
- Prefer one or two targeted prompt additions over a broad rewrite.
|
||||
- Treat reasoning effort as a last-mile knob. Start lower, then increase only after prompt-level fixes and evals.
|
||||
- Before increasing reasoning effort, first add a completeness contract, a verification loop, and tool persistence rules - depending on the usage case.
|
||||
- If the workflow clearly depends on implementation changes rather than prompt changes, treat it as blocked for prompt-only upgrade guidance.
|
||||
- Do not classify a case as blocked just because the workflow uses tools; block only if the upgrade requires changing tool definitions, wiring, or other implementation details.
|
||||
|
||||
## Behavioral differences to account for
|
||||
|
||||
Current GPT-5.4 upgrade guidance suggests these strengths:
|
||||
|
||||
- stronger personality and tone adherence, with less drift over long answers
|
||||
- better long-horizon and agentic workflow stamina
|
||||
- stronger spreadsheet, finance, and formatting tasks
|
||||
- more efficient tool selection and fewer unnecessary calls by default
|
||||
- stronger structured generation and classification reliability
|
||||
|
||||
The main places where prompt guidance still helps are:
|
||||
|
||||
- retrieval-heavy workflows that need persistent tool use and explicit completeness
|
||||
- research and citation discipline
|
||||
- verification before irreversible or high-impact actions
|
||||
- terminal and tool workflow hygiene
|
||||
- defaults and implied follow-through
|
||||
- verbosity control for compact, information-dense answers
|
||||
|
||||
Start with the smallest set of instructions that preserves correctness. Add the prompt blocks below only for workflows that actually need them.
|
||||
|
||||
## Prompt rewrite patterns
|
||||
|
||||
| Older prompt pattern | GPT-5.4 adjustment | Why | Example addition |
|
||||
| --- | --- | --- | --- |
|
||||
| Long, repetitive instructions that compensate for weaker instruction following | Remove duplicate scaffolding and keep only the constraints that materially change behavior | GPT-5.4 usually needs less repeated steering | Replace repeated reminders with one concise rule plus a verification block |
|
||||
| Fast assistant prompt with no verbosity control | Keep the prompt as-is first; add a verbosity clamp only if outputs become too long | Many GPT-4o or GPT-4.1 upgrades work with just a model-string swap | Add `output_verbosity_spec` only after a verbosity regression |
|
||||
| Tool-heavy agent prompt that assumes the model will keep searching until complete | Add persistence and verification rules | GPT-5.4 may use fewer tool calls by default for efficiency | Add `tool_persistence_rules` and `verification_loop` |
|
||||
| Tool-heavy workflow where later actions depend on earlier lookup or retrieval | Add prerequisite and missing-context rules before action steps | GPT-5.4 benefits from explicit dependency-aware routing when context is still thin | Add `dependency_checks` and `missing_context_gating` |
|
||||
| Retrieval workflow with several independent lookups | Add selective parallelism guidance | GPT-5.4 is strong at parallel tool use, but should not parallelize dependent steps | Add `parallel_tool_calling` |
|
||||
| Batch workflow prompt that often misses items | Add an explicit completeness contract | Item accounting benefits from direct instruction | Add `completeness_contract` |
|
||||
| Research prompt that needs grounding and citation discipline | Add research, citation, and empty-result recovery blocks | Multi-pass retrieval is stronger when the model is told how to react to weak or empty search results | Add `research_mode`, `citation_rules`, and `empty_result_handling`; add `tool_persistence_rules` when retrieval tools are already in use |
|
||||
| Coding or terminal prompt with shell misuse or early stop failures | Keep the same tool surface and add terminal hygiene and verification instructions | Tool-using coding workflows are not blocked just because tools exist; they usually need better prompt steering, not host rewiring | Add `terminal_tool_hygiene` and `verification_loop`, optionally `tool_persistence_rules` |
|
||||
| Multi-agent or support-triage workflow with escalation or completeness requirements | Add one lightweight control block for persistence, completeness, or verification | GPT-5.4 can be more efficient by default, so multi-step support flows benefit from an explicit completion or verification contract | Add at least one of `tool_persistence_rules`, `completeness_contract`, or `verification_loop` |
|
||||
|
||||
## Prompt blocks
|
||||
|
||||
Use these selectively. Do not add all of them by default.
|
||||
|
||||
### `output_verbosity_spec`
|
||||
|
||||
Use when:
|
||||
|
||||
- the upgraded model gets too wordy
|
||||
- the host needs compact, information-dense answers
|
||||
- the workflow benefits from a short overview plus a checklist
|
||||
|
||||
```text
|
||||
<output_verbosity_spec>
|
||||
- Default: 3-6 sentences or up to 6 bullets.
|
||||
- If the user asked for a doc or report, use headings with short bullets.
|
||||
- For multi-step tasks:
|
||||
- Start with 1 short overview paragraph.
|
||||
- Then provide a checklist with statuses: [done], [todo], or [blocked].
|
||||
- Avoid repeating the user's request.
|
||||
- Prefer compact, information-dense writing.
|
||||
</output_verbosity_spec>
|
||||
```
|
||||
|
||||
### `default_follow_through_policy`
|
||||
|
||||
Use when:
|
||||
|
||||
- the host expects the model to proceed on reversible, low-risk steps
|
||||
- the upgraded model becomes too conservative or asks for confirmation too often
|
||||
|
||||
```text
|
||||
<default_follow_through_policy>
|
||||
- If the user's intent is clear and the next step is reversible and low-risk, proceed without asking permission.
|
||||
- Only ask permission if the next step is:
|
||||
(a) irreversible,
|
||||
(b) has external side effects, or
|
||||
(c) requires missing sensitive information or a choice that materially changes outcomes.
|
||||
- If proceeding, state what you did and what remains optional.
|
||||
</default_follow_through_policy>
|
||||
```
|
||||
|
||||
### `instruction_priority`
|
||||
|
||||
Use when:
|
||||
|
||||
- users often change task shape, format, or tone mid-conversation
|
||||
- the host needs an explicit override policy instead of relying on defaults
|
||||
|
||||
```text
|
||||
<instruction_priority>
|
||||
- User instructions override default style, tone, formatting, and initiative preferences.
|
||||
- Safety, honesty, privacy, and permission constraints do not yield.
|
||||
- If a newer user instruction conflicts with an earlier one, follow the newer instruction.
|
||||
- Preserve earlier instructions that do not conflict.
|
||||
</instruction_priority>
|
||||
```
|
||||
|
||||
### `tool_persistence_rules`
|
||||
|
||||
Use when:
|
||||
|
||||
- the workflow needs multiple retrieval or verification steps
|
||||
- the model starts stopping too early because it is trying to save tool calls
|
||||
|
||||
```text
|
||||
<tool_persistence_rules>
|
||||
- Use tools whenever they materially improve correctness, completeness, or grounding.
|
||||
- Do not stop early just to save tool calls.
|
||||
- Keep calling tools until:
|
||||
(1) the task is complete, and
|
||||
(2) verification passes.
|
||||
- If a tool returns empty or partial results, retry with a different strategy.
|
||||
</tool_persistence_rules>
|
||||
```
|
||||
|
||||
### `dig_deeper_nudge`
|
||||
|
||||
Use when:
|
||||
|
||||
- the model is too literal or stops at the first plausible answer
|
||||
- the task is safety- or accuracy-sensitive and needs a small initiative nudge before raising reasoning effort
|
||||
|
||||
```text
|
||||
<dig_deeper_nudge>
|
||||
- Do not stop at the first plausible answer.
|
||||
- Look for second-order issues, edge cases, and missing constraints.
|
||||
- If the task is safety- or accuracy-critical, perform at least one verification step.
|
||||
</dig_deeper_nudge>
|
||||
```
|
||||
|
||||
### `dependency_checks`
|
||||
|
||||
Use when:
|
||||
|
||||
- later actions depend on prerequisite lookup, memory retrieval, or discovery steps
|
||||
- the model may be tempted to skip prerequisite work because the intended end state seems obvious
|
||||
|
||||
```text
|
||||
<dependency_checks>
|
||||
- Before taking an action, check whether prerequisite discovery, lookup, or memory retrieval is required.
|
||||
- Do not skip prerequisite steps just because the intended final action seems obvious.
|
||||
- If a later step depends on the output of an earlier one, resolve that dependency first.
|
||||
</dependency_checks>
|
||||
```
|
||||
|
||||
### `parallel_tool_calling`
|
||||
|
||||
Use when:
|
||||
|
||||
- the workflow has multiple independent retrieval steps
|
||||
- wall-clock time matters but some steps still need sequencing
|
||||
|
||||
```text
|
||||
<parallel_tool_calling>
|
||||
- When multiple retrieval or lookup steps are independent, prefer parallel tool calls to reduce wall-clock time.
|
||||
- Do not parallelize steps with prerequisite dependencies or where one result determines the next action.
|
||||
- After parallel retrieval, pause to synthesize before making more calls.
|
||||
- Prefer selective parallelism: parallelize independent evidence gathering, not speculative or redundant tool use.
|
||||
</parallel_tool_calling>
|
||||
```
|
||||
|
||||
### `completeness_contract`
|
||||
|
||||
Use when:
|
||||
|
||||
- the task involves batches, lists, enumerations, or multiple deliverables
|
||||
- missing items are a common failure mode
|
||||
|
||||
```text
|
||||
<completeness_contract>
|
||||
- Deliver all requested items.
|
||||
- Maintain an itemized checklist of deliverables.
|
||||
- For lists or batches:
|
||||
- state the expected count,
|
||||
- enumerate items 1..N,
|
||||
- confirm that none are missing before finalizing.
|
||||
- If any item is blocked by missing data, mark it [blocked] and state exactly what is missing.
|
||||
</completeness_contract>
|
||||
```
|
||||
|
||||
### `empty_result_handling`
|
||||
|
||||
Use when:
|
||||
|
||||
- the workflow frequently performs search, CRM, logs, or retrieval steps
|
||||
- no-results failures are often false negatives
|
||||
|
||||
```text
|
||||
<empty_result_handling>
|
||||
If a lookup returns empty or suspiciously small results:
|
||||
- Do not conclude that no results exist immediately.
|
||||
- Try at least 2 fallback strategies, such as a broader query, alternate filters, or another source.
|
||||
- Only then report that no results were found, along with what you tried.
|
||||
</empty_result_handling>
|
||||
```
|
||||
|
||||
### `verification_loop`
|
||||
|
||||
Use when:
|
||||
|
||||
- the workflow has downstream impact
|
||||
- accuracy, formatting, or completeness regressions matter
|
||||
|
||||
```text
|
||||
<verification_loop>
|
||||
Before finalizing:
|
||||
- Check correctness: does the output satisfy every requirement?
|
||||
- Check grounding: are factual claims backed by retrieved sources or tool output?
|
||||
- Check formatting: does the output match the requested schema or style?
|
||||
- Check safety and irreversibility: if the next step has external side effects, ask permission first.
|
||||
</verification_loop>
|
||||
```
|
||||
|
||||
### `missing_context_gating`
|
||||
|
||||
Use when:
|
||||
|
||||
- required context is sometimes missing early in the workflow
|
||||
- the model should prefer retrieval over guessing
|
||||
|
||||
```text
|
||||
<missing_context_gating>
|
||||
- If required context is missing, do not guess.
|
||||
- Prefer the appropriate lookup tool when the context is retrievable; ask a minimal clarifying question only when it is not.
|
||||
- If you must proceed, label assumptions explicitly and choose a reversible action.
|
||||
</missing_context_gating>
|
||||
```
|
||||
|
||||
### `action_safety`
|
||||
|
||||
Use when:
|
||||
|
||||
- the agent will actively take actions through tools
|
||||
- the host benefits from a short pre-flight and post-flight execution frame
|
||||
|
||||
```text
|
||||
<action_safety>
|
||||
- Pre-flight: summarize the intended action and parameters in 1-2 lines.
|
||||
- Execute via tool.
|
||||
- Post-flight: confirm the outcome and any validation that was performed.
|
||||
</action_safety>
|
||||
```
|
||||
|
||||
### `citation_rules`
|
||||
|
||||
Use when:
|
||||
|
||||
- the workflow produces cited answers
|
||||
- fabricated citations or wrong citation formats are costly
|
||||
|
||||
```text
|
||||
<citation_rules>
|
||||
- Only cite sources that were actually retrieved in this session.
|
||||
- Never fabricate citations, URLs, IDs, or quote spans.
|
||||
- If you cannot find a source for a claim, say so and either:
|
||||
- soften the claim, or
|
||||
- explain how to verify it with tools.
|
||||
- Use exactly the citation format required by the host application.
|
||||
</citation_rules>
|
||||
```
|
||||
|
||||
### `research_mode`
|
||||
|
||||
Use when:
|
||||
|
||||
- the workflow is research-heavy
|
||||
- the host uses web search or retrieval tools
|
||||
|
||||
```text
|
||||
<research_mode>
|
||||
- Do research in 3 passes:
|
||||
1) Plan: list 3-6 sub-questions to answer.
|
||||
2) Retrieve: search each sub-question and follow 1-2 second-order leads.
|
||||
3) Synthesize: resolve contradictions and write the final answer with citations.
|
||||
- Stop only when more searching is unlikely to change the conclusion.
|
||||
</research_mode>
|
||||
```
|
||||
|
||||
If your host environment uses a specific research tool or requires a submit step, combine this with the host's finalization contract.
|
||||
|
||||
### `structured_output_contract`
|
||||
|
||||
Use when:
|
||||
|
||||
- the host depends on strict JSON, SQL, or other structured output
|
||||
|
||||
```text
|
||||
<structured_output_contract>
|
||||
- Output only the requested format.
|
||||
- Do not add prose or markdown fences unless they were requested.
|
||||
- Validate that parentheses and brackets are balanced.
|
||||
- Do not invent tables or fields.
|
||||
- If required schema information is missing, ask for it or return an explicit error object.
|
||||
</structured_output_contract>
|
||||
```
|
||||
|
||||
### `bbox_extraction_spec`
|
||||
|
||||
Use when:
|
||||
|
||||
- the workflow extracts OCR boxes, document regions, or other coordinates
|
||||
- layout drift or missed dense regions are common failure modes
|
||||
|
||||
```text
|
||||
<bbox_extraction_spec>
|
||||
- Use the specified coordinate format exactly, such as [x1,y1,x2,y2] normalized to 0..1.
|
||||
- For each box, include page, label, text snippet, and confidence.
|
||||
- Add a vertical-drift sanity check so boxes stay aligned with the correct line of text.
|
||||
- If the layout is dense, process page by page and do a second pass for missed items.
|
||||
</bbox_extraction_spec>
|
||||
```
|
||||
|
||||
### `terminal_tool_hygiene`
|
||||
|
||||
Use when:
|
||||
|
||||
- the prompt belongs to a terminal-based or coding-agent workflow
|
||||
- tool misuse or shell misuse has been observed
|
||||
|
||||
```text
|
||||
<terminal_tool_hygiene>
|
||||
- Only run shell commands through the terminal tool.
|
||||
- Never try to "run" tool names as shell commands.
|
||||
- If a patch or edit tool exists, use it directly instead of emulating it in bash.
|
||||
- After changes, run a lightweight verification step such as ls, tests, or a build before declaring the task done.
|
||||
</terminal_tool_hygiene>
|
||||
```
|
||||
|
||||
### `user_updates_spec`
|
||||
|
||||
Use when:
|
||||
|
||||
- the workflow is long-running and user updates matter
|
||||
|
||||
```text
|
||||
<user_updates_spec>
|
||||
- Only update the user when starting a new major phase or when the plan changes.
|
||||
- Each update should contain:
|
||||
- 1 sentence on what changed,
|
||||
- 1 sentence on the next step.
|
||||
- Do not narrate routine tool calls.
|
||||
- Keep the user-facing update short, even when the actual work is exhaustive.
|
||||
</user_updates_spec>
|
||||
```
|
||||
|
||||
If you are using [Compaction](https://developers.openai.com/api/docs/guides/compaction) in the Responses API, compact after major milestones, treat compacted items as opaque state, and keep prompts functionally identical after compaction.
|
||||
|
||||
## Responses `phase` guidance
|
||||
|
||||
For long-running Responses workflows, preambles, or tool-heavy agents that replay assistant items, review whether `phase` is already preserved.
|
||||
|
||||
- If the host already round-trips `phase`, keep it intact during the upgrade.
|
||||
- If the host uses `previous_response_id` and does not manually replay assistant items, note that this may reduce manual `phase` handling needs.
|
||||
- If reliable GPT-5.4 behavior would require adding or preserving `phase` and that would need code edits, treat the case as blocked for prompt-only or model-string-only migration guidance.
|
||||
|
||||
## Example upgrade profiles
|
||||
|
||||
### GPT-5.2
|
||||
|
||||
- Use `gpt-5.4`
|
||||
- Match the current reasoning effort first
|
||||
- Preserve the existing latency and quality profile before tuning prompt blocks
|
||||
- If the repo does not expose the exact setting, emit `same` as the starting recommendation
|
||||
|
||||
### GPT-5.3-Codex
|
||||
|
||||
- Use `gpt-5.4`
|
||||
- Match the current reasoning effort first
|
||||
- If you need Codex-style speed and efficiency, add verification blocks before increasing reasoning effort
|
||||
- If the repo does not expose the exact setting, emit `same` as the starting recommendation
|
||||
|
||||
### GPT-4o or GPT-4.1 assistant
|
||||
|
||||
- Use `gpt-5.4`
|
||||
- Start with `none` reasoning effort
|
||||
- Add `output_verbosity_spec` only if output becomes too verbose
|
||||
|
||||
### Long-horizon agent
|
||||
|
||||
- Use `gpt-5.4`
|
||||
- Start with `medium` reasoning effort
|
||||
- Add `tool_persistence_rules`
|
||||
- Add `completeness_contract`
|
||||
- Add `verification_loop`
|
||||
|
||||
### Research workflow
|
||||
|
||||
- Use `gpt-5.4`
|
||||
- Start with `medium` reasoning effort
|
||||
- Add `research_mode`
|
||||
- Add `citation_rules`
|
||||
- Add `empty_result_handling`
|
||||
- Add `tool_persistence_rules` when the host already uses web or retrieval tools
|
||||
- Add `parallel_tool_calling` when the retrieval steps are independent
|
||||
|
||||
### Support triage or multi-agent workflow
|
||||
|
||||
- Use `gpt-5.4`
|
||||
- Prefer `model string + light prompt rewrite` over `model string only`
|
||||
- Add at least one of `tool_persistence_rules`, `completeness_contract`, or `verification_loop`
|
||||
- Add more only if evals show a real regression
|
||||
|
||||
### Coding or terminal workflow
|
||||
|
||||
- Use `gpt-5.4`
|
||||
- Keep the model-string change narrow
|
||||
- Match the current reasoning effort first if you are upgrading from GPT-5.3-Codex
|
||||
- Add `terminal_tool_hygiene`
|
||||
- Add `verification_loop`
|
||||
- Add `dependency_checks` when actions depend on prerequisite lookup or discovery
|
||||
- Add `tool_persistence_rules` if the agent stops too early
|
||||
- Review whether `phase` is already preserved for long-running Responses flows or assistant preambles
|
||||
- Do not classify this as blocked just because the workflow uses tools; block only if the upgrade requires changing tool definitions or wiring
|
||||
- If the repo already uses Responses plus tools and no required host-side change is shown, prefer `model_string_plus_light_prompt_rewrite` over `blocked`
|
||||
|
||||
## Prompt regression checklist
|
||||
|
||||
- Check whether the upgraded prompt still preserves the original task intent.
|
||||
- Check whether the new prompt is leaner, not just longer.
|
||||
- Check completeness, citation quality, dependency handling, verification behavior, and verbosity.
|
||||
- For long-running Responses agents, check whether `phase` handling is already in place or needs implementation work.
|
||||
- Confirm that each added prompt block addresses an observed regression.
|
||||
- Remove prompt blocks that are not earning their keep.
|
||||
@@ -0,0 +1,35 @@
|
||||
# Latest model guide
|
||||
|
||||
This file is a curated helper. Every recommendation here must be verified against current OpenAI docs before it is repeated to a user.
|
||||
|
||||
## Current model map
|
||||
|
||||
| Model ID | Use for |
|
||||
| --- | --- |
|
||||
| `gpt-5.4` | Default text plus reasoning for most new apps |
|
||||
| `gpt-5.4-pro` | Only when the user explicitly asks for maximum reasoning or quality; substantially slower and more expensive |
|
||||
| `gpt-5-mini` | Cheaper and faster reasoning with good quality |
|
||||
| `gpt-5-nano` | High-throughput simple tasks and classification |
|
||||
| `gpt-5.4` | Explicit no-reasoning text path via `reasoning.effort: none` |
|
||||
| `gpt-4.1-mini` | Cheaper no-reasoning text |
|
||||
| `gpt-4.1-nano` | Fastest and cheapest no-reasoning text |
|
||||
| `gpt-5.3-codex` | Agentic coding, code editing, and tool-heavy coding workflows |
|
||||
| `gpt-5.1-codex-mini` | Cheaper coding workflows |
|
||||
| `gpt-image-1.5` | Best image generation and edit quality |
|
||||
| `gpt-image-1-mini` | Cost-optimized image generation |
|
||||
| `gpt-4o-mini-tts` | Text-to-speech |
|
||||
| `gpt-4o-mini-transcribe` | Speech-to-text, fast and cost-efficient |
|
||||
| `gpt-realtime-1.5` | Realtime voice and multimodal sessions |
|
||||
| `gpt-realtime-mini` | Cheaper realtime sessions |
|
||||
| `gpt-audio` | Chat Completions audio input and output |
|
||||
| `gpt-audio-mini` | Cheaper Chat Completions audio workflows |
|
||||
| `sora-2` | Faster iteration and draft video generation |
|
||||
| `sora-2-pro` | Higher-quality production video |
|
||||
| `omni-moderation-latest` | Text and image moderation |
|
||||
| `text-embedding-3-large` | Higher-quality retrieval embeddings; default in this skill because no best-specific row exists |
|
||||
| `text-embedding-3-small` | Lower-cost embeddings |
|
||||
|
||||
## Maintenance notes
|
||||
|
||||
- This file will drift unless it is periodically re-verified against current OpenAI docs.
|
||||
- If this file conflicts with current docs, the docs win.
|
||||
@@ -0,0 +1,164 @@
|
||||
# Upgrading to GPT-5.4
|
||||
|
||||
Use this guide when the user explicitly asks to upgrade an existing integration to GPT-5.4. Pair it with current OpenAI docs lookups. The default target string is `gpt-5.4`.
|
||||
|
||||
## Upgrade posture
|
||||
|
||||
Upgrade with the narrowest safe change set:
|
||||
|
||||
- replace the model string first
|
||||
- update only the prompts that are directly tied to that model usage
|
||||
- prefer prompt-only upgrades when possible
|
||||
- if the upgrade would require API-surface changes, parameter rewrites, tool rewiring, or broader code edits, mark it as blocked instead of stretching the scope
|
||||
|
||||
## Upgrade workflow
|
||||
|
||||
1. Inventory current model usage.
|
||||
- Search for model strings, client calls, and prompt-bearing files.
|
||||
- Include inline prompts, prompt templates, YAML or JSON configs, Markdown docs, and saved prompts when they are clearly tied to a model usage site.
|
||||
2. Pair each model usage with its prompt surface.
|
||||
- Prefer the closest prompt surface first: inline system or developer text, then adjacent prompt files, then shared templates.
|
||||
- If you cannot confidently tie a prompt to the model usage, say so instead of guessing.
|
||||
3. Classify the source model family.
|
||||
- Common buckets: `gpt-4o` or `gpt-4.1`, `o1` or `o3` or `o4-mini`, early `gpt-5`, later `gpt-5.x`, or mixed and unclear.
|
||||
4. Decide the upgrade class.
|
||||
- `model string only`
|
||||
- `model string + light prompt rewrite`
|
||||
- `blocked without code changes`
|
||||
5. Run the no-code compatibility gate.
|
||||
- Check whether the current integration can accept `gpt-5.4` without API-surface changes or implementation changes.
|
||||
- For long-running Responses or tool-heavy agents, check whether `phase` is already preserved or round-tripped when the host replays assistant items or uses preambles.
|
||||
- If compatibility depends on code changes, return `blocked`.
|
||||
- If compatibility is unclear, return `unknown` rather than improvising.
|
||||
6. Recommend the upgrade.
|
||||
- Default replacement string: `gpt-5.4`
|
||||
- Keep the intervention small and behavior-preserving.
|
||||
7. Deliver a structured recommendation.
|
||||
- `Current model usage`
|
||||
- `Recommended model-string updates`
|
||||
- `Starting reasoning recommendation`
|
||||
- `Prompt updates`
|
||||
- `Phase assessment` when the flow is long-running, replayed, or tool-heavy
|
||||
- `No-code compatibility check`
|
||||
- `Validation plan`
|
||||
- `Launch-day refresh items`
|
||||
|
||||
Output rule:
|
||||
|
||||
- Always emit a starting `reasoning_effort_recommendation` for each usage site.
|
||||
- If the repo exposes the current reasoning setting, preserve it first unless the source guide says otherwise.
|
||||
- If the repo does not expose the current setting, use the source-family starting mapping instead of returning `null`.
|
||||
|
||||
## Upgrade outcomes
|
||||
|
||||
### `model string only`
|
||||
|
||||
Choose this when:
|
||||
|
||||
- the existing prompts are already short, explicit, and task-bounded
|
||||
- the workflow is not strongly research-heavy, tool-heavy, multi-agent, batch or completeness-sensitive, or long-horizon
|
||||
- there are no obvious compatibility blockers
|
||||
|
||||
Default action:
|
||||
|
||||
- replace the model string with `gpt-5.4`
|
||||
- keep prompts unchanged
|
||||
- validate behavior with existing evals or spot checks
|
||||
|
||||
### `model string + light prompt rewrite`
|
||||
|
||||
Choose this when:
|
||||
|
||||
- the old prompt was compensating for weaker instruction following
|
||||
- the workflow needs more persistence than the default tool-use behavior will likely provide
|
||||
- the task needs stronger completeness, citation discipline, or verification
|
||||
- the upgraded model becomes too verbose or under-complete unless instructed otherwise
|
||||
- the workflow is research-heavy and needs stronger handling of sparse or empty retrieval results
|
||||
- the workflow is coding-oriented, tool-heavy, or multi-agent, but the existing API surface and tool definitions can remain unchanged
|
||||
|
||||
Default action:
|
||||
|
||||
- replace the model string with `gpt-5.4`
|
||||
- add one or two targeted prompt blocks
|
||||
- read `references/gpt-5p4-prompting-guide.md` to choose the smallest prompt changes that recover the old behavior
|
||||
- avoid broad prompt cleanup unrelated to the upgrade
|
||||
- for research workflows, default to `research_mode` + `citation_rules` + `empty_result_handling`; add `tool_persistence_rules` when the host already uses retrieval tools
|
||||
- for dependency-aware or tool-heavy workflows, default to `tool_persistence_rules` + `dependency_checks` + `verification_loop`; add `parallel_tool_calling` only when retrieval steps are truly independent
|
||||
- for coding or terminal workflows, default to `terminal_tool_hygiene` + `verification_loop`
|
||||
- for multi-agent support or triage workflows, default to at least one of `tool_persistence_rules`, `completeness_contract`, or `verification_loop`
|
||||
- for long-running Responses agents with preambles or multiple assistant messages, explicitly review whether `phase` is already handled; if adding or preserving `phase` would require code edits, mark the path as `blocked`
|
||||
- do not classify a coding or tool-using Responses workflow as `blocked` just because the visible snippet is minimal; prefer `model string + light prompt rewrite` unless the repo clearly shows that a safe GPT-5.4 path would require host-side code changes
|
||||
|
||||
### `blocked`
|
||||
|
||||
Choose this when:
|
||||
|
||||
- the upgrade appears to require API-surface changes
|
||||
- the upgrade appears to require parameter rewrites or reasoning-setting changes that are not exposed outside implementation code
|
||||
- the upgrade would require changing tool definitions, tool handler wiring, or schema contracts
|
||||
- you cannot confidently identify the prompt surface tied to the model usage
|
||||
|
||||
Default action:
|
||||
|
||||
- do not improvise a broader upgrade
|
||||
- report the blocker and explain that the fix is out of scope for this guide
|
||||
|
||||
## No-code compatibility checklist
|
||||
|
||||
Before recommending a no-code upgrade, check:
|
||||
|
||||
1. Can the current host accept the `gpt-5.4` model string without changing client code or API surface?
|
||||
2. Are the related prompts identifiable and editable?
|
||||
3. Does the host depend on behavior that likely needs API-surface changes, parameter rewrites, or tool rewiring?
|
||||
4. Would the likely fix be prompt-only, or would it need implementation changes?
|
||||
5. Is the prompt surface close enough to the model usage that you can make a targeted change instead of a broad cleanup?
|
||||
6. For long-running Responses or tool-heavy agents, is `phase` already preserved if the host relies on preambles, replayed assistant items, or multiple assistant messages?
|
||||
|
||||
If item 1 is no, items 3 through 4 point to implementation work, or item 6 is no and the fix needs code changes, return `blocked`.
|
||||
|
||||
If item 2 is no, return `unknown` unless the user can point to the prompt location.
|
||||
|
||||
Important:
|
||||
|
||||
- Existing use of tools, agents, or multiple usage sites is not by itself a blocker.
|
||||
- If the current host can keep the same API surface and the same tool definitions, prefer `model string + light prompt rewrite` over `blocked`.
|
||||
- Reserve `blocked` for cases that truly require implementation changes, not cases that only need stronger prompt steering.
|
||||
|
||||
## Scope boundaries
|
||||
|
||||
This guide may:
|
||||
|
||||
- update or recommend updated model strings
|
||||
- update or recommend updated prompts
|
||||
- inspect code and prompt files to understand where those changes belong
|
||||
- inspect whether existing Responses flows already preserve `phase`
|
||||
- flag compatibility blockers
|
||||
|
||||
This guide may not:
|
||||
|
||||
- move Chat Completions code to Responses
|
||||
- move Responses code to another API surface
|
||||
- rewrite parameter shapes
|
||||
- change tool definitions or tool-call handling
|
||||
- change structured-output wiring
|
||||
- add or retrofit `phase` handling in implementation code
|
||||
- edit business logic, orchestration logic, or SDK usage beyond a literal model-string replacement
|
||||
|
||||
If a safe GPT-5.4 upgrade requires any of those changes, mark the path as blocked and out of scope.
|
||||
|
||||
## Validation plan
|
||||
|
||||
- Validate each upgraded usage site with existing evals or realistic spot checks.
|
||||
- Check whether the upgraded model still matches expected latency, output shape, and quality.
|
||||
- If prompt edits were added, confirm each block is doing real work instead of adding noise.
|
||||
- If the workflow has downstream impact, add a lightweight verification pass before finalization.
|
||||
|
||||
## Launch-day refresh items
|
||||
|
||||
When final GPT-5.4 guidance changes:
|
||||
|
||||
1. Replace release-candidate assumptions with final GPT-5.4 guidance where appropriate.
|
||||
2. Re-check whether the default target string should stay `gpt-5.4` for all source families.
|
||||
3. Re-check any prompt-block recommendations whose semantics may have changed.
|
||||
4. Re-check research, citation, and compatibility guidance against the final model behavior.
|
||||
5. Re-run the same upgrade scenarios and confirm the blocked-versus-viable boundaries still hold.
|
||||
413
.agents/skills/.system/skill-creator/SKILL.md
Normal file
413
.agents/skills/.system/skill-creator/SKILL.md
Normal file
@@ -0,0 +1,413 @@
|
||||
---
|
||||
name: skill-creator
|
||||
description: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.
|
||||
metadata:
|
||||
short-description: Create or update a skill
|
||||
---
|
||||
|
||||
# Skill Creator
|
||||
|
||||
This skill provides guidance for creating effective skills.
|
||||
|
||||
## About Skills
|
||||
|
||||
Skills are modular, self-contained folders that extend Codex's capabilities by providing
|
||||
specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific
|
||||
domains or tasks—they transform Codex from a general-purpose agent into a specialized agent
|
||||
equipped with procedural knowledge that no model can fully possess.
|
||||
|
||||
### What Skills Provide
|
||||
|
||||
1. Specialized workflows - Multi-step procedures for specific domains
|
||||
2. Tool integrations - Instructions for working with specific file formats or APIs
|
||||
3. Domain expertise - Company-specific knowledge, schemas, business logic
|
||||
4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks
|
||||
|
||||
## Core Principles
|
||||
|
||||
### Concise is Key
|
||||
|
||||
The context window is a public good. Skills share the context window with everything else Codex needs: system prompt, conversation history, other Skills' metadata, and the actual user request.
|
||||
|
||||
**Default assumption: Codex is already very smart.** Only add context Codex doesn't already have. Challenge each piece of information: "Does Codex really need this explanation?" and "Does this paragraph justify its token cost?"
|
||||
|
||||
Prefer concise examples over verbose explanations.
|
||||
|
||||
### Set Appropriate Degrees of Freedom
|
||||
|
||||
Match the level of specificity to the task's fragility and variability:
|
||||
|
||||
**High freedom (text-based instructions)**: Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.
|
||||
|
||||
**Medium freedom (pseudocode or scripts with parameters)**: Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.
|
||||
|
||||
**Low freedom (specific scripts, few parameters)**: Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.
|
||||
|
||||
Think of Codex as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).
|
||||
|
||||
### Protect Validation Integrity
|
||||
|
||||
You may use subagents during iteration to validate whether a skill works on realistic tasks or whether a suspected problem is real. This is most useful when you want an independent pass on the skill's behavior, outputs, or failure modes after a revision. Only do this when it is possible to start new subagents.
|
||||
|
||||
When using subagents for validation, treat that as an evaluation surface. The goal is to learn whether the skill generalizes, not whether another agent can reconstruct the answer from leaked context.
|
||||
|
||||
Prefer raw artifacts such as example prompts, outputs, diffs, logs, or traces. Give the minimum task-local context needed to perform the validation. Avoid passing the intended answer, suspected bug, intended fix, or your prior conclusions unless the validation explicitly requires them.
|
||||
|
||||
### Anatomy of a Skill
|
||||
|
||||
Every skill consists of a required SKILL.md file and optional bundled resources:
|
||||
|
||||
```
|
||||
skill-name/
|
||||
├── SKILL.md (required)
|
||||
│ ├── YAML frontmatter metadata (required)
|
||||
│ │ ├── name: (required)
|
||||
│ │ └── description: (required)
|
||||
│ └── Markdown instructions (required)
|
||||
├── agents/ (recommended)
|
||||
│ └── openai.yaml - UI metadata for skill lists and chips
|
||||
└── Bundled Resources (optional)
|
||||
├── scripts/ - Executable code (Python/Bash/etc.)
|
||||
├── references/ - Documentation intended to be loaded into context as needed
|
||||
└── assets/ - Files used in output (templates, icons, fonts, etc.)
|
||||
```
|
||||
|
||||
#### SKILL.md (required)
|
||||
|
||||
Every SKILL.md consists of:
|
||||
|
||||
- **Frontmatter** (YAML): Contains `name` and `description` fields. These are the only fields that Codex reads to determine when the skill gets used, thus it is very important to be clear and comprehensive in describing what the skill is, and when it should be used.
|
||||
- **Body** (Markdown): Instructions and guidance for using the skill. Only loaded AFTER the skill triggers (if at all).
|
||||
|
||||
#### Agents metadata (recommended)
|
||||
|
||||
- UI-facing metadata for skill lists and chips
|
||||
- Read references/openai_yaml.md before generating values and follow its descriptions and constraints
|
||||
- Create: human-facing `display_name`, `short_description`, and `default_prompt` by reading the skill
|
||||
- Generate deterministically by passing the values as `--interface key=value` to `scripts/generate_openai_yaml.py` or `scripts/init_skill.py`
|
||||
- On updates: validate `agents/openai.yaml` still matches SKILL.md; regenerate if stale
|
||||
- Only include other optional interface fields (icons, brand color) if explicitly provided
|
||||
- See references/openai_yaml.md for field definitions and examples
|
||||
|
||||
#### Bundled Resources (optional)
|
||||
|
||||
##### Scripts (`scripts/`)
|
||||
|
||||
Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.
|
||||
|
||||
- **When to include**: When the same code is being rewritten repeatedly or deterministic reliability is needed
|
||||
- **Example**: `scripts/rotate_pdf.py` for PDF rotation tasks
|
||||
- **Benefits**: Token efficient, deterministic, may be executed without loading into context
|
||||
- **Note**: Scripts may still need to be read by Codex for patching or environment-specific adjustments
|
||||
|
||||
##### References (`references/`)
|
||||
|
||||
Documentation and reference material intended to be loaded as needed into context to inform Codex's process and thinking.
|
||||
|
||||
- **When to include**: For documentation that Codex should reference while working
|
||||
- **Examples**: `references/finance.md` for financial schemas, `references/mnda.md` for company NDA template, `references/policies.md` for company policies, `references/api_docs.md` for API specifications
|
||||
- **Use cases**: Database schemas, API documentation, domain knowledge, company policies, detailed workflow guides
|
||||
- **Benefits**: Keeps SKILL.md lean, loaded only when Codex determines it's needed
|
||||
- **Best practice**: If files are large (>10k words), include grep search patterns in SKILL.md
|
||||
- **Avoid duplication**: Information should live in either SKILL.md or references files, not both. Prefer references files for detailed information unless it's truly core to the skill—this keeps SKILL.md lean while making information discoverable without hogging the context window. Keep only essential procedural instructions and workflow guidance in SKILL.md; move detailed reference material, schemas, and examples to references files.
|
||||
|
||||
##### Assets (`assets/`)
|
||||
|
||||
Files not intended to be loaded into context, but rather used within the output Codex produces.
|
||||
|
||||
- **When to include**: When the skill needs files that will be used in the final output
|
||||
- **Examples**: `assets/logo.png` for brand assets, `assets/slides.pptx` for PowerPoint templates, `assets/frontend-template/` for HTML/React boilerplate, `assets/font.ttf` for typography
|
||||
- **Use cases**: Templates, images, icons, boilerplate code, fonts, sample documents that get copied or modified
|
||||
- **Benefits**: Separates output resources from documentation, enables Codex to use files without loading them into context
|
||||
|
||||
#### What to Not Include in a Skill
|
||||
|
||||
A skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:
|
||||
|
||||
- README.md
|
||||
- INSTALLATION_GUIDE.md
|
||||
- QUICK_REFERENCE.md
|
||||
- CHANGELOG.md
|
||||
- etc.
|
||||
|
||||
The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxiliary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.
|
||||
|
||||
### Progressive Disclosure Design Principle
|
||||
|
||||
Skills use a three-level loading system to manage context efficiently:
|
||||
|
||||
1. **Metadata (name + description)** - Always in context (~100 words)
|
||||
2. **SKILL.md body** - When skill triggers (<5k words)
|
||||
3. **Bundled resources** - As needed by Codex (Unlimited because scripts can be executed without reading into context window)
|
||||
|
||||
#### Progressive Disclosure Patterns
|
||||
|
||||
Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them.
|
||||
|
||||
**Key principle:** When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files.
|
||||
|
||||
**Pattern 1: High-level guide with references**
|
||||
|
||||
```markdown
|
||||
# PDF Processing
|
||||
|
||||
## Quick start
|
||||
|
||||
Extract text with pdfplumber:
|
||||
[code example]
|
||||
|
||||
## Advanced features
|
||||
|
||||
- **Form filling**: See [FORMS.md](FORMS.md) for complete guide
|
||||
- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods
|
||||
- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns
|
||||
```
|
||||
|
||||
Codex loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed.
|
||||
|
||||
**Pattern 2: Domain-specific organization**
|
||||
|
||||
For Skills with multiple domains, organize content by domain to avoid loading irrelevant context:
|
||||
|
||||
```
|
||||
bigquery-skill/
|
||||
├── SKILL.md (overview and navigation)
|
||||
└── reference/
|
||||
├── finance.md (revenue, billing metrics)
|
||||
├── sales.md (opportunities, pipeline)
|
||||
├── product.md (API usage, features)
|
||||
└── marketing.md (campaigns, attribution)
|
||||
```
|
||||
|
||||
When a user asks about sales metrics, Codex only reads sales.md.
|
||||
|
||||
Similarly, for skills supporting multiple frameworks or variants, organize by variant:
|
||||
|
||||
```
|
||||
cloud-deploy/
|
||||
├── SKILL.md (workflow + provider selection)
|
||||
└── references/
|
||||
├── aws.md (AWS deployment patterns)
|
||||
├── gcp.md (GCP deployment patterns)
|
||||
└── azure.md (Azure deployment patterns)
|
||||
```
|
||||
|
||||
When the user chooses AWS, Codex only reads aws.md.
|
||||
|
||||
**Pattern 3: Conditional details**
|
||||
|
||||
Show basic content, link to advanced content:
|
||||
|
||||
```markdown
|
||||
# DOCX Processing
|
||||
|
||||
## Creating documents
|
||||
|
||||
Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).
|
||||
|
||||
## Editing documents
|
||||
|
||||
For simple edits, modify the XML directly.
|
||||
|
||||
**For tracked changes**: See [REDLINING.md](REDLINING.md)
|
||||
**For OOXML details**: See [OOXML.md](OOXML.md)
|
||||
```
|
||||
|
||||
Codex reads REDLINING.md or OOXML.md only when the user needs those features.
|
||||
|
||||
**Important guidelines:**
|
||||
|
||||
- **Avoid deeply nested references** - Keep references one level deep from SKILL.md. All reference files should link directly from SKILL.md.
|
||||
- **Structure longer reference files** - For files longer than 100 lines, include a table of contents at the top so Codex can see the full scope when previewing.
|
||||
|
||||
## Skill Creation Process
|
||||
|
||||
Skill creation involves these steps:
|
||||
|
||||
1. Understand the skill with concrete examples
|
||||
2. Plan reusable skill contents (scripts, references, assets)
|
||||
3. Initialize the skill (run init_skill.py)
|
||||
4. Edit the skill (implement resources and write SKILL.md)
|
||||
5. Validate the skill (run quick_validate.py)
|
||||
6. Iterate based on real usage and forward-test complex skills.
|
||||
|
||||
Follow these steps in order, skipping only if there is a clear reason why they are not applicable.
|
||||
|
||||
### Skill Naming
|
||||
|
||||
- Use lowercase letters, digits, and hyphens only; normalize user-provided titles to hyphen-case (e.g., "Plan Mode" -> `plan-mode`).
|
||||
- When generating names, generate a name under 64 characters (letters, digits, hyphens).
|
||||
- Prefer short, verb-led phrases that describe the action.
|
||||
- Namespace by tool when it improves clarity or triggering (e.g., `gh-address-comments`, `linear-address-issue`).
|
||||
- Name the skill folder exactly after the skill name.
|
||||
|
||||
### Step 1: Understanding the Skill with Concrete Examples
|
||||
|
||||
Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill.
|
||||
|
||||
To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.
|
||||
|
||||
For example, when building an image-editor skill, relevant questions include:
|
||||
|
||||
- "What functionality should the image-editor skill support? Editing, rotating, anything else?"
|
||||
- "Can you give some examples of how this skill would be used?"
|
||||
- "I can imagine users asking for things like 'Remove the red-eye from this image' or 'Rotate this image'. Are there other ways you imagine this skill being used?"
|
||||
- "What would a user say that should trigger this skill?"
|
||||
|
||||
To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness.
|
||||
|
||||
Conclude this step when there is a clear sense of the functionality the skill should support.
|
||||
|
||||
### Step 2: Planning the Reusable Skill Contents
|
||||
|
||||
To turn concrete examples into an effective skill, analyze each example by:
|
||||
|
||||
1. Considering how to execute on the example from scratch
|
||||
2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly
|
||||
|
||||
Example: When building a `pdf-editor` skill to handle queries like "Help me rotate this PDF," the analysis shows:
|
||||
|
||||
1. Rotating a PDF requires re-writing the same code each time
|
||||
2. A `scripts/rotate_pdf.py` script would be helpful to store in the skill
|
||||
|
||||
Example: When designing a `frontend-webapp-builder` skill for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows:
|
||||
|
||||
1. Writing a frontend webapp requires the same boilerplate HTML/React each time
|
||||
2. An `assets/hello-world/` template containing the boilerplate HTML/React project files would be helpful to store in the skill
|
||||
|
||||
Example: When building a `big-query` skill to handle queries like "How many users have logged in today?" the analysis shows:
|
||||
|
||||
1. Querying BigQuery requires re-discovering the table schemas and relationships each time
|
||||
2. A `references/schema.md` file documenting the table schemas would be helpful to store in the skill
|
||||
|
||||
To establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.
|
||||
|
||||
### Step 3: Initializing the Skill
|
||||
|
||||
At this point, it is time to actually create the skill.
|
||||
|
||||
Skip this step only if the skill being developed already exists. In this case, continue to the next step.
|
||||
|
||||
When creating a new skill from scratch, always run the `init_skill.py` script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable.
|
||||
|
||||
Usage:
|
||||
|
||||
```bash
|
||||
scripts/init_skill.py <skill-name> --path <output-directory> [--resources scripts,references,assets] [--examples]
|
||||
```
|
||||
|
||||
Examples:
|
||||
|
||||
```bash
|
||||
scripts/init_skill.py my-skill --path skills/public
|
||||
scripts/init_skill.py my-skill --path skills/public --resources scripts,references
|
||||
scripts/init_skill.py my-skill --path skills/public --resources scripts --examples
|
||||
```
|
||||
|
||||
The script:
|
||||
|
||||
- Creates the skill directory at the specified path
|
||||
- Generates a SKILL.md template with proper frontmatter and TODO placeholders
|
||||
- Creates `agents/openai.yaml` using agent-generated `display_name`, `short_description`, and `default_prompt` passed via `--interface key=value`
|
||||
- Optionally creates resource directories based on `--resources`
|
||||
- Optionally adds example files when `--examples` is set
|
||||
|
||||
After initialization, customize the SKILL.md and add resources as needed. If you used `--examples`, replace or delete placeholder files.
|
||||
|
||||
Generate `display_name`, `short_description`, and `default_prompt` by reading the skill, then pass them as `--interface key=value` to `init_skill.py` or regenerate with:
|
||||
|
||||
```bash
|
||||
scripts/generate_openai_yaml.py <path/to/skill-folder> --interface key=value
|
||||
```
|
||||
|
||||
Only include other optional interface fields when the user explicitly provides them. For full field descriptions and examples, see references/openai_yaml.md.
|
||||
|
||||
### Step 4: Edit the Skill
|
||||
|
||||
When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Codex to use. Include information that would be beneficial and non-obvious to Codex. Consider what procedural knowledge, domain-specific details, or reusable assets would help another Codex instance execute these tasks more effectively.
|
||||
|
||||
After substantial revisions, or if the skill is particularly tricky, you should use subagents to forward-test the skill on realistic tasks or artifacts. When doing so, pass the artifact under validation rather than your diagnosis of what is wrong, and keep the prompt generic enough that success depends on transferable reasoning rather than hidden ground truth.
|
||||
|
||||
#### Start with Reusable Skill Contents
|
||||
|
||||
To begin implementation, start with the reusable resources identified above: `scripts/`, `references/`, and `assets/` files. Note that this step may require user input. For example, when implementing a `brand-guidelines` skill, the user may need to provide brand assets or templates to store in `assets/`, or documentation to store in `references/`.
|
||||
|
||||
Added scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion.
|
||||
|
||||
If you used `--examples`, delete any placeholder files that are not needed for the skill. Only create resource directories that are actually required.
|
||||
|
||||
#### Update SKILL.md
|
||||
|
||||
**Writing Guidelines:** Always use imperative/infinitive form.
|
||||
|
||||
##### Frontmatter
|
||||
|
||||
Write the YAML frontmatter with `name` and `description`:
|
||||
|
||||
- `name`: The skill name
|
||||
- `description`: This is the primary triggering mechanism for your skill, and helps Codex understand when to use the skill.
|
||||
- Include both what the Skill does and specific triggers/contexts for when to use it.
|
||||
- Include all "when to use" information here - Not in the body. The body is only loaded after triggering, so "When to Use This Skill" sections in the body are not helpful to Codex.
|
||||
- Example description for a `docx` skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when Codex needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks"
|
||||
|
||||
Do not include any other fields in YAML frontmatter.
|
||||
|
||||
##### Body
|
||||
|
||||
Write instructions for using the skill and its bundled resources.
|
||||
|
||||
### Step 5: Validate the Skill
|
||||
|
||||
Once development of the skill is complete, validate the skill folder to catch basic issues early:
|
||||
|
||||
```bash
|
||||
scripts/quick_validate.py <path/to/skill-folder>
|
||||
```
|
||||
|
||||
The validation script checks YAML frontmatter format, required fields, and naming rules. If validation fails, fix the reported issues and run the command again.
|
||||
|
||||
### Step 6: Iterate
|
||||
|
||||
After testing the skill, you may detect the skill is complex enough that it requires forward-testing; or users may request improvements.
|
||||
|
||||
User testing often this happens right after using the skill, with fresh context of how the skill performed.
|
||||
|
||||
**Forward-testing and iteration workflow:**
|
||||
|
||||
1. Use the skill on real tasks
|
||||
2. Notice struggles or inefficiencies
|
||||
3. Identify how SKILL.md or bundled resources should be updated
|
||||
4. Implement changes and test again
|
||||
5. Forward-test if it is reasonable and appropriate
|
||||
|
||||
## Forward-testing
|
||||
|
||||
To forward-test, launch subagents as a way to stress test the skill with minimal context.
|
||||
Subagents should *not* know that they are being asked to test the skill. They should be treated as
|
||||
an agent asked to perform a task by the user. Prompts to subagents should look like:
|
||||
`Use $skill-x at /path/to/skill-x to solve problem y`
|
||||
Not:
|
||||
`Review the skill at /path/to/skill-x; pretend a user asks you to...`
|
||||
|
||||
Decision rule for forward-testing:
|
||||
- Err on the side of forward-testing
|
||||
- Ask for approval if you think there's a risk that forward-testing would:
|
||||
* take a long time,
|
||||
* require additional approvals from the user, or
|
||||
* modify live production systems
|
||||
|
||||
In these cases, show the user your proposed prompt and request (1) a yes/no decision, and
|
||||
(2) any suggested modifictions.
|
||||
|
||||
Considerations when forward-testing:
|
||||
- use fresh threads for independent passes
|
||||
- pass the skill, and a request in a similar way the user would.
|
||||
- pass raw artifacts, not your conclusions
|
||||
- avoid showing expected answers or intended fixes
|
||||
- rebuild context from source artifacts after each iteration
|
||||
- review the subagent's output and reasoning and emitted artifacts
|
||||
- avoid leaving artifacts the agent can find on disk between iterations;
|
||||
clean up subagents' artifacts to avoid additional contamination.
|
||||
|
||||
If forward-testing only succeeds when subagents see leaked context, tighten the skill or the
|
||||
forward-testing setup before trusting the result.
|
||||
5
.agents/skills/.system/skill-creator/agents/openai.yaml
Normal file
5
.agents/skills/.system/skill-creator/agents/openai.yaml
Normal file
@@ -0,0 +1,5 @@
|
||||
interface:
|
||||
display_name: "Skill Creator"
|
||||
short_description: "Create or update a skill"
|
||||
icon_small: "./assets/skill-creator-small.svg"
|
||||
icon_large: "./assets/skill-creator.png"
|
||||
@@ -0,0 +1,3 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="currentColor" viewBox="0 0 20 20">
|
||||
<path fill="#0D0D0D" d="M12.03 4.113a3.612 3.612 0 0 1 5.108 5.108l-6.292 6.29c-.324.324-.56.561-.791.752l-.235.176c-.205.14-.422.261-.65.36l-.229.093a4.136 4.136 0 0 1-.586.16l-.764.134-2.394.4c-.142.024-.294.05-.423.06-.098.007-.232.01-.378-.026l-.149-.05a1.081 1.081 0 0 1-.521-.474l-.046-.093a1.104 1.104 0 0 1-.075-.527c.01-.129.035-.28.06-.422l.398-2.394c.1-.602.162-.987.295-1.35l.093-.23c.1-.228.22-.445.36-.65l.176-.235c.19-.232.428-.467.751-.79l6.292-6.292Zm-5.35 7.232c-.35.35-.534.535-.66.688l-.11.147a2.67 2.67 0 0 0-.24.433l-.062.154c-.08.22-.124.462-.232 1.112l-.398 2.394-.001.001h.003l2.393-.399.717-.126a2.63 2.63 0 0 0 .394-.105l.154-.063a2.65 2.65 0 0 0 .433-.24l.147-.11c.153-.126.339-.31.688-.66l4.988-4.988-3.227-3.226-4.987 4.988Zm9.517-6.291a2.281 2.281 0 0 0-3.225 0l-.364.362 3.226 3.227.363-.364c.89-.89.89-2.334 0-3.225ZM4.583 1.783a.3.3 0 0 1 .294.241c.117.585.347 1.092.707 1.48.357.385.859.668 1.549.783a.3.3 0 0 1 0 .592c-.69.115-1.192.398-1.549.783-.315.34-.53.77-.657 1.265l-.05.215a.3.3 0 0 1-.588 0c-.117-.585-.347-1.092-.707-1.48-.357-.384-.859-.668-1.549-.783a.3.3 0 0 1 0-.592c.69-.115 1.192-.398 1.549-.783.36-.388.59-.895.707-1.48l.015-.05a.3.3 0 0 1 .279-.19Z"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 1.3 KiB |
BIN
.agents/skills/.system/skill-creator/assets/skill-creator.png
Normal file
BIN
.agents/skills/.system/skill-creator/assets/skill-creator.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 1.5 KiB |
202
.agents/skills/.system/skill-creator/license.txt
Normal file
202
.agents/skills/.system/skill-creator/license.txt
Normal file
@@ -0,0 +1,202 @@
|
||||
|
||||
Apache License
|
||||
Version 2.0, January 2004
|
||||
http://www.apache.org/licenses/
|
||||
|
||||
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||
|
||||
1. Definitions.
|
||||
|
||||
"License" shall mean the terms and conditions for use, reproduction,
|
||||
and distribution as defined by Sections 1 through 9 of this document.
|
||||
|
||||
"Licensor" shall mean the copyright owner or entity authorized by
|
||||
the copyright owner that is granting the License.
|
||||
|
||||
"Legal Entity" shall mean the union of the acting entity and all
|
||||
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|
||||
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|
||||
"control" means (i) the power, direct or indirect, to cause the
|
||||
direction or management of such entity, whether by contract or
|
||||
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|
||||
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|
||||
|
||||
"You" (or "Your") shall mean an individual or Legal Entity
|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
|
||||
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|
||||
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||||
|
||||
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|
||||
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|
||||
|
||||
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|
||||
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||||
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|
||||
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|
||||
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||||
|
||||
(d) If the Work includes a "NOTICE" text file as part of its
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
Notwithstanding the above, nothing herein shall supersede or modify
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||||
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||||
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||||
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END OF TERMS AND CONDITIONS
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||||
APPENDIX: How to apply the Apache License to your work.
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||||
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||||
To apply the Apache License to your work, attach the following
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||||
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||||
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||||
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||||
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|
||||
@@ -0,0 +1,49 @@
|
||||
# openai.yaml fields (full example + descriptions)
|
||||
|
||||
`agents/openai.yaml` is an extended, product-specific config intended for the machine/harness to read, not the agent. Other product-specific config can also live in the `agents/` folder.
|
||||
|
||||
## Full example
|
||||
|
||||
```yaml
|
||||
interface:
|
||||
display_name: "Optional user-facing name"
|
||||
short_description: "Optional user-facing description"
|
||||
icon_small: "./assets/small-400px.png"
|
||||
icon_large: "./assets/large-logo.svg"
|
||||
brand_color: "#3B82F6"
|
||||
default_prompt: "Optional surrounding prompt to use the skill with"
|
||||
|
||||
dependencies:
|
||||
tools:
|
||||
- type: "mcp"
|
||||
value: "github"
|
||||
description: "GitHub MCP server"
|
||||
transport: "streamable_http"
|
||||
url: "https://api.githubcopilot.com/mcp/"
|
||||
|
||||
policy:
|
||||
allow_implicit_invocation: true
|
||||
```
|
||||
|
||||
## Field descriptions and constraints
|
||||
|
||||
Top-level constraints:
|
||||
|
||||
- Quote all string values.
|
||||
- Keep keys unquoted.
|
||||
- For `interface.default_prompt`: generate a helpful, short (typically 1 sentence) example starting prompt based on the skill. It must explicitly mention the skill as `$skill-name` (e.g., "Use $skill-name-here to draft a concise weekly status update.").
|
||||
|
||||
- `interface.display_name`: Human-facing title shown in UI skill lists and chips.
|
||||
- `interface.short_description`: Human-facing short UI blurb (25–64 chars) for quick scanning.
|
||||
- `interface.icon_small`: Path to a small icon asset (relative to skill dir). Default to `./assets/` and place icons in the skill's `assets/` folder.
|
||||
- `interface.icon_large`: Path to a larger logo asset (relative to skill dir). Default to `./assets/` and place icons in the skill's `assets/` folder.
|
||||
- `interface.brand_color`: Hex color used for UI accents (e.g., badges).
|
||||
- `interface.default_prompt`: Default prompt snippet inserted when invoking the skill.
|
||||
- `dependencies.tools[].type`: Dependency category. Only `mcp` is supported for now.
|
||||
- `dependencies.tools[].value`: Identifier of the tool or dependency.
|
||||
- `dependencies.tools[].description`: Human-readable explanation of the dependency.
|
||||
- `dependencies.tools[].transport`: Connection type when `type` is `mcp`.
|
||||
- `dependencies.tools[].url`: MCP server URL when `type` is `mcp`.
|
||||
- `policy.allow_implicit_invocation`: When false, the skill is not injected into
|
||||
the model context by default, but can still be invoked explicitly via `$skill`.
|
||||
Defaults to true.
|
||||
@@ -0,0 +1,226 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
OpenAI YAML Generator - Creates agents/openai.yaml for a skill folder.
|
||||
|
||||
Usage:
|
||||
generate_openai_yaml.py <skill_dir> [--name <skill_name>] [--interface key=value]
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import re
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
ACRONYMS = {
|
||||
"GH",
|
||||
"MCP",
|
||||
"API",
|
||||
"CI",
|
||||
"CLI",
|
||||
"LLM",
|
||||
"PDF",
|
||||
"PR",
|
||||
"UI",
|
||||
"URL",
|
||||
"SQL",
|
||||
}
|
||||
|
||||
BRANDS = {
|
||||
"openai": "OpenAI",
|
||||
"openapi": "OpenAPI",
|
||||
"github": "GitHub",
|
||||
"pagerduty": "PagerDuty",
|
||||
"datadog": "DataDog",
|
||||
"sqlite": "SQLite",
|
||||
"fastapi": "FastAPI",
|
||||
}
|
||||
|
||||
SMALL_WORDS = {"and", "or", "to", "up", "with"}
|
||||
|
||||
ALLOWED_INTERFACE_KEYS = {
|
||||
"display_name",
|
||||
"short_description",
|
||||
"icon_small",
|
||||
"icon_large",
|
||||
"brand_color",
|
||||
"default_prompt",
|
||||
}
|
||||
|
||||
|
||||
def yaml_quote(value):
|
||||
escaped = value.replace("\\", "\\\\").replace('"', '\\"').replace("\n", "\\n")
|
||||
return f'"{escaped}"'
|
||||
|
||||
|
||||
def format_display_name(skill_name):
|
||||
words = [word for word in skill_name.split("-") if word]
|
||||
formatted = []
|
||||
for index, word in enumerate(words):
|
||||
lower = word.lower()
|
||||
upper = word.upper()
|
||||
if upper in ACRONYMS:
|
||||
formatted.append(upper)
|
||||
continue
|
||||
if lower in BRANDS:
|
||||
formatted.append(BRANDS[lower])
|
||||
continue
|
||||
if index > 0 and lower in SMALL_WORDS:
|
||||
formatted.append(lower)
|
||||
continue
|
||||
formatted.append(word.capitalize())
|
||||
return " ".join(formatted)
|
||||
|
||||
|
||||
def generate_short_description(display_name):
|
||||
description = f"Help with {display_name} tasks"
|
||||
|
||||
if len(description) < 25:
|
||||
description = f"Help with {display_name} tasks and workflows"
|
||||
if len(description) < 25:
|
||||
description = f"Help with {display_name} tasks with guidance"
|
||||
|
||||
if len(description) > 64:
|
||||
description = f"Help with {display_name}"
|
||||
if len(description) > 64:
|
||||
description = f"{display_name} helper"
|
||||
if len(description) > 64:
|
||||
description = f"{display_name} tools"
|
||||
if len(description) > 64:
|
||||
suffix = " helper"
|
||||
max_name_length = 64 - len(suffix)
|
||||
trimmed = display_name[:max_name_length].rstrip()
|
||||
description = f"{trimmed}{suffix}"
|
||||
if len(description) > 64:
|
||||
description = description[:64].rstrip()
|
||||
|
||||
if len(description) < 25:
|
||||
description = f"{description} workflows"
|
||||
if len(description) > 64:
|
||||
description = description[:64].rstrip()
|
||||
|
||||
return description
|
||||
|
||||
|
||||
def read_frontmatter_name(skill_dir):
|
||||
skill_md = Path(skill_dir) / "SKILL.md"
|
||||
if not skill_md.exists():
|
||||
print(f"[ERROR] SKILL.md not found in {skill_dir}")
|
||||
return None
|
||||
content = skill_md.read_text()
|
||||
match = re.match(r"^---\n(.*?)\n---", content, re.DOTALL)
|
||||
if not match:
|
||||
print("[ERROR] Invalid SKILL.md frontmatter format.")
|
||||
return None
|
||||
frontmatter_text = match.group(1)
|
||||
|
||||
import yaml
|
||||
|
||||
try:
|
||||
frontmatter = yaml.safe_load(frontmatter_text)
|
||||
except yaml.YAMLError as exc:
|
||||
print(f"[ERROR] Invalid YAML frontmatter: {exc}")
|
||||
return None
|
||||
if not isinstance(frontmatter, dict):
|
||||
print("[ERROR] Frontmatter must be a YAML dictionary.")
|
||||
return None
|
||||
name = frontmatter.get("name", "")
|
||||
if not isinstance(name, str) or not name.strip():
|
||||
print("[ERROR] Frontmatter 'name' is missing or invalid.")
|
||||
return None
|
||||
return name.strip()
|
||||
|
||||
|
||||
def parse_interface_overrides(raw_overrides):
|
||||
overrides = {}
|
||||
optional_order = []
|
||||
for item in raw_overrides:
|
||||
if "=" not in item:
|
||||
print(f"[ERROR] Invalid interface override '{item}'. Use key=value.")
|
||||
return None, None
|
||||
key, value = item.split("=", 1)
|
||||
key = key.strip()
|
||||
value = value.strip()
|
||||
if not key:
|
||||
print(f"[ERROR] Invalid interface override '{item}'. Key is empty.")
|
||||
return None, None
|
||||
if key not in ALLOWED_INTERFACE_KEYS:
|
||||
allowed = ", ".join(sorted(ALLOWED_INTERFACE_KEYS))
|
||||
print(f"[ERROR] Unknown interface field '{key}'. Allowed: {allowed}")
|
||||
return None, None
|
||||
overrides[key] = value
|
||||
if key not in ("display_name", "short_description") and key not in optional_order:
|
||||
optional_order.append(key)
|
||||
return overrides, optional_order
|
||||
|
||||
|
||||
def write_openai_yaml(skill_dir, skill_name, raw_overrides):
|
||||
overrides, optional_order = parse_interface_overrides(raw_overrides)
|
||||
if overrides is None:
|
||||
return None
|
||||
|
||||
display_name = overrides.get("display_name") or format_display_name(skill_name)
|
||||
short_description = overrides.get("short_description") or generate_short_description(display_name)
|
||||
|
||||
if not (25 <= len(short_description) <= 64):
|
||||
print(
|
||||
"[ERROR] short_description must be 25-64 characters "
|
||||
f"(got {len(short_description)})."
|
||||
)
|
||||
return None
|
||||
|
||||
interface_lines = [
|
||||
"interface:",
|
||||
f" display_name: {yaml_quote(display_name)}",
|
||||
f" short_description: {yaml_quote(short_description)}",
|
||||
]
|
||||
|
||||
for key in optional_order:
|
||||
value = overrides.get(key)
|
||||
if value is not None:
|
||||
interface_lines.append(f" {key}: {yaml_quote(value)}")
|
||||
|
||||
agents_dir = Path(skill_dir) / "agents"
|
||||
agents_dir.mkdir(parents=True, exist_ok=True)
|
||||
output_path = agents_dir / "openai.yaml"
|
||||
output_path.write_text("\n".join(interface_lines) + "\n")
|
||||
print(f"[OK] Created agents/openai.yaml")
|
||||
return output_path
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Create agents/openai.yaml for a skill directory.",
|
||||
)
|
||||
parser.add_argument("skill_dir", help="Path to the skill directory")
|
||||
parser.add_argument(
|
||||
"--name",
|
||||
help="Skill name override (defaults to SKILL.md frontmatter)",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--interface",
|
||||
action="append",
|
||||
default=[],
|
||||
help="Interface override in key=value format (repeatable)",
|
||||
)
|
||||
args = parser.parse_args()
|
||||
|
||||
skill_dir = Path(args.skill_dir).resolve()
|
||||
if not skill_dir.exists():
|
||||
print(f"[ERROR] Skill directory not found: {skill_dir}")
|
||||
sys.exit(1)
|
||||
if not skill_dir.is_dir():
|
||||
print(f"[ERROR] Path is not a directory: {skill_dir}")
|
||||
sys.exit(1)
|
||||
|
||||
skill_name = args.name or read_frontmatter_name(skill_dir)
|
||||
if not skill_name:
|
||||
sys.exit(1)
|
||||
|
||||
result = write_openai_yaml(skill_dir, skill_name, args.interface)
|
||||
if result:
|
||||
sys.exit(0)
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
400
.agents/skills/.system/skill-creator/scripts/init_skill.py
Normal file
400
.agents/skills/.system/skill-creator/scripts/init_skill.py
Normal file
@@ -0,0 +1,400 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Skill Initializer - Creates a new skill from template
|
||||
|
||||
Usage:
|
||||
init_skill.py <skill-name> --path <path> [--resources scripts,references,assets] [--examples] [--interface key=value]
|
||||
|
||||
Examples:
|
||||
init_skill.py my-new-skill --path skills/public
|
||||
init_skill.py my-new-skill --path skills/public --resources scripts,references
|
||||
init_skill.py my-api-helper --path skills/private --resources scripts --examples
|
||||
init_skill.py custom-skill --path /custom/location
|
||||
init_skill.py my-skill --path skills/public --interface short_description="Short UI label"
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import re
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
from generate_openai_yaml import write_openai_yaml
|
||||
|
||||
MAX_SKILL_NAME_LENGTH = 64
|
||||
ALLOWED_RESOURCES = {"scripts", "references", "assets"}
|
||||
|
||||
SKILL_TEMPLATE = """---
|
||||
name: {skill_name}
|
||||
description: [TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.]
|
||||
---
|
||||
|
||||
# {skill_title}
|
||||
|
||||
## Overview
|
||||
|
||||
[TODO: 1-2 sentences explaining what this skill enables]
|
||||
|
||||
## Structuring This Skill
|
||||
|
||||
[TODO: Choose the structure that best fits this skill's purpose. Common patterns:
|
||||
|
||||
**1. Workflow-Based** (best for sequential processes)
|
||||
- Works well when there are clear step-by-step procedures
|
||||
- Example: DOCX skill with "Workflow Decision Tree" -> "Reading" -> "Creating" -> "Editing"
|
||||
- Structure: ## Overview -> ## Workflow Decision Tree -> ## Step 1 -> ## Step 2...
|
||||
|
||||
**2. Task-Based** (best for tool collections)
|
||||
- Works well when the skill offers different operations/capabilities
|
||||
- Example: PDF skill with "Quick Start" -> "Merge PDFs" -> "Split PDFs" -> "Extract Text"
|
||||
- Structure: ## Overview -> ## Quick Start -> ## Task Category 1 -> ## Task Category 2...
|
||||
|
||||
**3. Reference/Guidelines** (best for standards or specifications)
|
||||
- Works well for brand guidelines, coding standards, or requirements
|
||||
- Example: Brand styling with "Brand Guidelines" -> "Colors" -> "Typography" -> "Features"
|
||||
- Structure: ## Overview -> ## Guidelines -> ## Specifications -> ## Usage...
|
||||
|
||||
**4. Capabilities-Based** (best for integrated systems)
|
||||
- Works well when the skill provides multiple interrelated features
|
||||
- Example: Product Management with "Core Capabilities" -> numbered capability list
|
||||
- Structure: ## Overview -> ## Core Capabilities -> ### 1. Feature -> ### 2. Feature...
|
||||
|
||||
Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations).
|
||||
|
||||
Delete this entire "Structuring This Skill" section when done - it's just guidance.]
|
||||
|
||||
## [TODO: Replace with the first main section based on chosen structure]
|
||||
|
||||
[TODO: Add content here. See examples in existing skills:
|
||||
- Code samples for technical skills
|
||||
- Decision trees for complex workflows
|
||||
- Concrete examples with realistic user requests
|
||||
- References to scripts/templates/references as needed]
|
||||
|
||||
## Resources (optional)
|
||||
|
||||
Create only the resource directories this skill actually needs. Delete this section if no resources are required.
|
||||
|
||||
### scripts/
|
||||
Executable code (Python/Bash/etc.) that can be run directly to perform specific operations.
|
||||
|
||||
**Examples from other skills:**
|
||||
- PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation
|
||||
- DOCX skill: `document.py`, `utilities.py` - Python modules for document processing
|
||||
|
||||
**Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations.
|
||||
|
||||
**Note:** Scripts may be executed without loading into context, but can still be read by Codex for patching or environment adjustments.
|
||||
|
||||
### references/
|
||||
Documentation and reference material intended to be loaded into context to inform Codex's process and thinking.
|
||||
|
||||
**Examples from other skills:**
|
||||
- Product management: `communication.md`, `context_building.md` - detailed workflow guides
|
||||
- BigQuery: API reference documentation and query examples
|
||||
- Finance: Schema documentation, company policies
|
||||
|
||||
**Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Codex should reference while working.
|
||||
|
||||
### assets/
|
||||
Files not intended to be loaded into context, but rather used within the output Codex produces.
|
||||
|
||||
**Examples from other skills:**
|
||||
- Brand styling: PowerPoint template files (.pptx), logo files
|
||||
- Frontend builder: HTML/React boilerplate project directories
|
||||
- Typography: Font files (.ttf, .woff2)
|
||||
|
||||
**Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output.
|
||||
|
||||
---
|
||||
|
||||
**Not every skill requires all three types of resources.**
|
||||
"""
|
||||
|
||||
EXAMPLE_SCRIPT = '''#!/usr/bin/env python3
|
||||
"""
|
||||
Example helper script for {skill_name}
|
||||
|
||||
This is a placeholder script that can be executed directly.
|
||||
Replace with actual implementation or delete if not needed.
|
||||
|
||||
Example real scripts from other skills:
|
||||
- pdf/scripts/fill_fillable_fields.py - Fills PDF form fields
|
||||
- pdf/scripts/convert_pdf_to_images.py - Converts PDF pages to images
|
||||
"""
|
||||
|
||||
def main():
|
||||
print("This is an example script for {skill_name}")
|
||||
# TODO: Add actual script logic here
|
||||
# This could be data processing, file conversion, API calls, etc.
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
'''
|
||||
|
||||
EXAMPLE_REFERENCE = """# Reference Documentation for {skill_title}
|
||||
|
||||
This is a placeholder for detailed reference documentation.
|
||||
Replace with actual reference content or delete if not needed.
|
||||
|
||||
Example real reference docs from other skills:
|
||||
- product-management/references/communication.md - Comprehensive guide for status updates
|
||||
- product-management/references/context_building.md - Deep-dive on gathering context
|
||||
- bigquery/references/ - API references and query examples
|
||||
|
||||
## When Reference Docs Are Useful
|
||||
|
||||
Reference docs are ideal for:
|
||||
- Comprehensive API documentation
|
||||
- Detailed workflow guides
|
||||
- Complex multi-step processes
|
||||
- Information too lengthy for main SKILL.md
|
||||
- Content that's only needed for specific use cases
|
||||
|
||||
## Structure Suggestions
|
||||
|
||||
### API Reference Example
|
||||
- Overview
|
||||
- Authentication
|
||||
- Endpoints with examples
|
||||
- Error codes
|
||||
- Rate limits
|
||||
|
||||
### Workflow Guide Example
|
||||
- Prerequisites
|
||||
- Step-by-step instructions
|
||||
- Common patterns
|
||||
- Troubleshooting
|
||||
- Best practices
|
||||
"""
|
||||
|
||||
EXAMPLE_ASSET = """# Example Asset File
|
||||
|
||||
This placeholder represents where asset files would be stored.
|
||||
Replace with actual asset files (templates, images, fonts, etc.) or delete if not needed.
|
||||
|
||||
Asset files are NOT intended to be loaded into context, but rather used within
|
||||
the output Codex produces.
|
||||
|
||||
Example asset files from other skills:
|
||||
- Brand guidelines: logo.png, slides_template.pptx
|
||||
- Frontend builder: hello-world/ directory with HTML/React boilerplate
|
||||
- Typography: custom-font.ttf, font-family.woff2
|
||||
- Data: sample_data.csv, test_dataset.json
|
||||
|
||||
## Common Asset Types
|
||||
|
||||
- Templates: .pptx, .docx, boilerplate directories
|
||||
- Images: .png, .jpg, .svg, .gif
|
||||
- Fonts: .ttf, .otf, .woff, .woff2
|
||||
- Boilerplate code: Project directories, starter files
|
||||
- Icons: .ico, .svg
|
||||
- Data files: .csv, .json, .xml, .yaml
|
||||
|
||||
Note: This is a text placeholder. Actual assets can be any file type.
|
||||
"""
|
||||
|
||||
|
||||
def normalize_skill_name(skill_name):
|
||||
"""Normalize a skill name to lowercase hyphen-case."""
|
||||
normalized = skill_name.strip().lower()
|
||||
normalized = re.sub(r"[^a-z0-9]+", "-", normalized)
|
||||
normalized = normalized.strip("-")
|
||||
normalized = re.sub(r"-{2,}", "-", normalized)
|
||||
return normalized
|
||||
|
||||
|
||||
def title_case_skill_name(skill_name):
|
||||
"""Convert hyphenated skill name to Title Case for display."""
|
||||
return " ".join(word.capitalize() for word in skill_name.split("-"))
|
||||
|
||||
|
||||
def parse_resources(raw_resources):
|
||||
if not raw_resources:
|
||||
return []
|
||||
resources = [item.strip() for item in raw_resources.split(",") if item.strip()]
|
||||
invalid = sorted({item for item in resources if item not in ALLOWED_RESOURCES})
|
||||
if invalid:
|
||||
allowed = ", ".join(sorted(ALLOWED_RESOURCES))
|
||||
print(f"[ERROR] Unknown resource type(s): {', '.join(invalid)}")
|
||||
print(f" Allowed: {allowed}")
|
||||
sys.exit(1)
|
||||
deduped = []
|
||||
seen = set()
|
||||
for resource in resources:
|
||||
if resource not in seen:
|
||||
deduped.append(resource)
|
||||
seen.add(resource)
|
||||
return deduped
|
||||
|
||||
|
||||
def create_resource_dirs(skill_dir, skill_name, skill_title, resources, include_examples):
|
||||
for resource in resources:
|
||||
resource_dir = skill_dir / resource
|
||||
resource_dir.mkdir(exist_ok=True)
|
||||
if resource == "scripts":
|
||||
if include_examples:
|
||||
example_script = resource_dir / "example.py"
|
||||
example_script.write_text(EXAMPLE_SCRIPT.format(skill_name=skill_name))
|
||||
example_script.chmod(0o755)
|
||||
print("[OK] Created scripts/example.py")
|
||||
else:
|
||||
print("[OK] Created scripts/")
|
||||
elif resource == "references":
|
||||
if include_examples:
|
||||
example_reference = resource_dir / "api_reference.md"
|
||||
example_reference.write_text(EXAMPLE_REFERENCE.format(skill_title=skill_title))
|
||||
print("[OK] Created references/api_reference.md")
|
||||
else:
|
||||
print("[OK] Created references/")
|
||||
elif resource == "assets":
|
||||
if include_examples:
|
||||
example_asset = resource_dir / "example_asset.txt"
|
||||
example_asset.write_text(EXAMPLE_ASSET)
|
||||
print("[OK] Created assets/example_asset.txt")
|
||||
else:
|
||||
print("[OK] Created assets/")
|
||||
|
||||
|
||||
def init_skill(skill_name, path, resources, include_examples, interface_overrides):
|
||||
"""
|
||||
Initialize a new skill directory with template SKILL.md.
|
||||
|
||||
Args:
|
||||
skill_name: Name of the skill
|
||||
path: Path where the skill directory should be created
|
||||
resources: Resource directories to create
|
||||
include_examples: Whether to create example files in resource directories
|
||||
|
||||
Returns:
|
||||
Path to created skill directory, or None if error
|
||||
"""
|
||||
# Determine skill directory path
|
||||
skill_dir = Path(path).resolve() / skill_name
|
||||
|
||||
# Check if directory already exists
|
||||
if skill_dir.exists():
|
||||
print(f"[ERROR] Skill directory already exists: {skill_dir}")
|
||||
return None
|
||||
|
||||
# Create skill directory
|
||||
try:
|
||||
skill_dir.mkdir(parents=True, exist_ok=False)
|
||||
print(f"[OK] Created skill directory: {skill_dir}")
|
||||
except Exception as e:
|
||||
print(f"[ERROR] Error creating directory: {e}")
|
||||
return None
|
||||
|
||||
# Create SKILL.md from template
|
||||
skill_title = title_case_skill_name(skill_name)
|
||||
skill_content = SKILL_TEMPLATE.format(skill_name=skill_name, skill_title=skill_title)
|
||||
|
||||
skill_md_path = skill_dir / "SKILL.md"
|
||||
try:
|
||||
skill_md_path.write_text(skill_content)
|
||||
print("[OK] Created SKILL.md")
|
||||
except Exception as e:
|
||||
print(f"[ERROR] Error creating SKILL.md: {e}")
|
||||
return None
|
||||
|
||||
# Create agents/openai.yaml
|
||||
try:
|
||||
result = write_openai_yaml(skill_dir, skill_name, interface_overrides)
|
||||
if not result:
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f"[ERROR] Error creating agents/openai.yaml: {e}")
|
||||
return None
|
||||
|
||||
# Create resource directories if requested
|
||||
if resources:
|
||||
try:
|
||||
create_resource_dirs(skill_dir, skill_name, skill_title, resources, include_examples)
|
||||
except Exception as e:
|
||||
print(f"[ERROR] Error creating resource directories: {e}")
|
||||
return None
|
||||
|
||||
# Print next steps
|
||||
print(f"\n[OK] Skill '{skill_name}' initialized successfully at {skill_dir}")
|
||||
print("\nNext steps:")
|
||||
print("1. Edit SKILL.md to complete the TODO items and update the description")
|
||||
if resources:
|
||||
if include_examples:
|
||||
print("2. Customize or delete the example files in scripts/, references/, and assets/")
|
||||
else:
|
||||
print("2. Add resources to scripts/, references/, and assets/ as needed")
|
||||
else:
|
||||
print("2. Create resource directories only if needed (scripts/, references/, assets/)")
|
||||
print("3. Update agents/openai.yaml if the UI metadata should differ")
|
||||
print("4. Run the validator when ready to check the skill structure")
|
||||
print(
|
||||
"5. Forward-test complex skills with realistic user requests to ensure they work as intended"
|
||||
)
|
||||
|
||||
return skill_dir
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Create a new skill directory with a SKILL.md template.",
|
||||
)
|
||||
parser.add_argument("skill_name", help="Skill name (normalized to hyphen-case)")
|
||||
parser.add_argument("--path", required=True, help="Output directory for the skill")
|
||||
parser.add_argument(
|
||||
"--resources",
|
||||
default="",
|
||||
help="Comma-separated list: scripts,references,assets",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--examples",
|
||||
action="store_true",
|
||||
help="Create example files inside the selected resource directories",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--interface",
|
||||
action="append",
|
||||
default=[],
|
||||
help="Interface override in key=value format (repeatable)",
|
||||
)
|
||||
args = parser.parse_args()
|
||||
|
||||
raw_skill_name = args.skill_name
|
||||
skill_name = normalize_skill_name(raw_skill_name)
|
||||
if not skill_name:
|
||||
print("[ERROR] Skill name must include at least one letter or digit.")
|
||||
sys.exit(1)
|
||||
if len(skill_name) > MAX_SKILL_NAME_LENGTH:
|
||||
print(
|
||||
f"[ERROR] Skill name '{skill_name}' is too long ({len(skill_name)} characters). "
|
||||
f"Maximum is {MAX_SKILL_NAME_LENGTH} characters."
|
||||
)
|
||||
sys.exit(1)
|
||||
if skill_name != raw_skill_name:
|
||||
print(f"Note: Normalized skill name from '{raw_skill_name}' to '{skill_name}'.")
|
||||
|
||||
resources = parse_resources(args.resources)
|
||||
if args.examples and not resources:
|
||||
print("[ERROR] --examples requires --resources to be set.")
|
||||
sys.exit(1)
|
||||
|
||||
path = args.path
|
||||
|
||||
print(f"Initializing skill: {skill_name}")
|
||||
print(f" Location: {path}")
|
||||
if resources:
|
||||
print(f" Resources: {', '.join(resources)}")
|
||||
if args.examples:
|
||||
print(" Examples: enabled")
|
||||
else:
|
||||
print(" Resources: none (create as needed)")
|
||||
print()
|
||||
|
||||
result = init_skill(skill_name, path, resources, args.examples, args.interface)
|
||||
|
||||
if result:
|
||||
sys.exit(0)
|
||||
else:
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
101
.agents/skills/.system/skill-creator/scripts/quick_validate.py
Normal file
101
.agents/skills/.system/skill-creator/scripts/quick_validate.py
Normal file
@@ -0,0 +1,101 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Quick validation script for skills - minimal version
|
||||
"""
|
||||
|
||||
import re
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
import yaml
|
||||
|
||||
MAX_SKILL_NAME_LENGTH = 64
|
||||
|
||||
|
||||
def validate_skill(skill_path):
|
||||
"""Basic validation of a skill"""
|
||||
skill_path = Path(skill_path)
|
||||
|
||||
skill_md = skill_path / "SKILL.md"
|
||||
if not skill_md.exists():
|
||||
return False, "SKILL.md not found"
|
||||
|
||||
content = skill_md.read_text()
|
||||
if not content.startswith("---"):
|
||||
return False, "No YAML frontmatter found"
|
||||
|
||||
match = re.match(r"^---\n(.*?)\n---", content, re.DOTALL)
|
||||
if not match:
|
||||
return False, "Invalid frontmatter format"
|
||||
|
||||
frontmatter_text = match.group(1)
|
||||
|
||||
try:
|
||||
frontmatter = yaml.safe_load(frontmatter_text)
|
||||
if not isinstance(frontmatter, dict):
|
||||
return False, "Frontmatter must be a YAML dictionary"
|
||||
except yaml.YAMLError as e:
|
||||
return False, f"Invalid YAML in frontmatter: {e}"
|
||||
|
||||
allowed_properties = {"name", "description", "license", "allowed-tools", "metadata"}
|
||||
|
||||
unexpected_keys = set(frontmatter.keys()) - allowed_properties
|
||||
if unexpected_keys:
|
||||
allowed = ", ".join(sorted(allowed_properties))
|
||||
unexpected = ", ".join(sorted(unexpected_keys))
|
||||
return (
|
||||
False,
|
||||
f"Unexpected key(s) in SKILL.md frontmatter: {unexpected}. Allowed properties are: {allowed}",
|
||||
)
|
||||
|
||||
if "name" not in frontmatter:
|
||||
return False, "Missing 'name' in frontmatter"
|
||||
if "description" not in frontmatter:
|
||||
return False, "Missing 'description' in frontmatter"
|
||||
|
||||
name = frontmatter.get("name", "")
|
||||
if not isinstance(name, str):
|
||||
return False, f"Name must be a string, got {type(name).__name__}"
|
||||
name = name.strip()
|
||||
if name:
|
||||
if not re.match(r"^[a-z0-9-]+$", name):
|
||||
return (
|
||||
False,
|
||||
f"Name '{name}' should be hyphen-case (lowercase letters, digits, and hyphens only)",
|
||||
)
|
||||
if name.startswith("-") or name.endswith("-") or "--" in name:
|
||||
return (
|
||||
False,
|
||||
f"Name '{name}' cannot start/end with hyphen or contain consecutive hyphens",
|
||||
)
|
||||
if len(name) > MAX_SKILL_NAME_LENGTH:
|
||||
return (
|
||||
False,
|
||||
f"Name is too long ({len(name)} characters). "
|
||||
f"Maximum is {MAX_SKILL_NAME_LENGTH} characters.",
|
||||
)
|
||||
|
||||
description = frontmatter.get("description", "")
|
||||
if not isinstance(description, str):
|
||||
return False, f"Description must be a string, got {type(description).__name__}"
|
||||
description = description.strip()
|
||||
if description:
|
||||
if "<" in description or ">" in description:
|
||||
return False, "Description cannot contain angle brackets (< or >)"
|
||||
if len(description) > 1024:
|
||||
return (
|
||||
False,
|
||||
f"Description is too long ({len(description)} characters). Maximum is 1024 characters.",
|
||||
)
|
||||
|
||||
return True, "Skill is valid!"
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
if len(sys.argv) != 2:
|
||||
print("Usage: python quick_validate.py <skill_directory>")
|
||||
sys.exit(1)
|
||||
|
||||
valid, message = validate_skill(sys.argv[1])
|
||||
print(message)
|
||||
sys.exit(0 if valid else 1)
|
||||
202
.agents/skills/.system/skill-installer/LICENSE.txt
Normal file
202
.agents/skills/.system/skill-installer/LICENSE.txt
Normal file
@@ -0,0 +1,202 @@
|
||||
|
||||
Apache License
|
||||
Version 2.0, January 2004
|
||||
http://www.apache.org/licenses/
|
||||
|
||||
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||
|
||||
1. Definitions.
|
||||
|
||||
"License" shall mean the terms and conditions for use, reproduction,
|
||||
and distribution as defined by Sections 1 through 9 of this document.
|
||||
|
||||
"Licensor" shall mean the copyright owner or entity authorized by
|
||||
the copyright owner that is granting the License.
|
||||
|
||||
"Legal Entity" shall mean the union of the acting entity and all
|
||||
other entities that control, are controlled by, or are under common
|
||||
control with that entity. For the purposes of this definition,
|
||||
"control" means (i) the power, direct or indirect, to cause the
|
||||
direction or management of such entity, whether by contract or
|
||||
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
||||
outstanding shares, or (iii) beneficial ownership of such entity.
|
||||
|
||||
"You" (or "Your") shall mean an individual or Legal Entity
|
||||
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|
||||
|
||||
"Source" form shall mean the preferred form for making modifications,
|
||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
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||||
"Work" shall mean the work of authorship, whether in Source or
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|
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|
||||
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||||
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||||
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|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
You may obtain a copy of the License at
|
||||
|
||||
http://www.apache.org/licenses/LICENSE-2.0
|
||||
|
||||
Unless required by applicable law or agreed to in writing, software
|
||||
distributed under the License is distributed on an "AS IS" BASIS,
|
||||
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
See the License for the specific language governing permissions and
|
||||
limitations under the License.
|
||||
58
.agents/skills/.system/skill-installer/SKILL.md
Normal file
58
.agents/skills/.system/skill-installer/SKILL.md
Normal file
@@ -0,0 +1,58 @@
|
||||
---
|
||||
name: skill-installer
|
||||
description: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
|
||||
metadata:
|
||||
short-description: Install curated skills from openai/skills or other repos
|
||||
---
|
||||
|
||||
# Skill Installer
|
||||
|
||||
Helps install skills. By default these are from https://github.com/openai/skills/tree/main/skills/.curated, but users can also provide other locations. Experimental skills live in https://github.com/openai/skills/tree/main/skills/.experimental and can be installed the same way.
|
||||
|
||||
Use the helper scripts based on the task:
|
||||
- List skills when the user asks what is available, or if the user uses this skill without specifying what to do. Default listing is `.curated`, but you can pass `--path skills/.experimental` when they ask about experimental skills.
|
||||
- Install from the curated list when the user provides a skill name.
|
||||
- Install from another repo when the user provides a GitHub repo/path (including private repos).
|
||||
|
||||
Install skills with the helper scripts.
|
||||
|
||||
## Communication
|
||||
|
||||
When listing skills, output approximately as follows, depending on the context of the user's request. If they ask about experimental skills, list from `.experimental` instead of `.curated` and label the source accordingly:
|
||||
"""
|
||||
Skills from {repo}:
|
||||
1. skill-1
|
||||
2. skill-2 (already installed)
|
||||
3. ...
|
||||
Which ones would you like installed?
|
||||
"""
|
||||
|
||||
After installing a skill, tell the user: "Restart Codex to pick up new skills."
|
||||
|
||||
## Scripts
|
||||
|
||||
All of these scripts use network, so when running in the sandbox, request escalation when running them.
|
||||
|
||||
- `scripts/list-skills.py` (prints skills list with installed annotations)
|
||||
- `scripts/list-skills.py --format json`
|
||||
- Example (experimental list): `scripts/list-skills.py --path skills/.experimental`
|
||||
- `scripts/install-skill-from-github.py --repo <owner>/<repo> --path <path/to/skill> [<path/to/skill> ...]`
|
||||
- `scripts/install-skill-from-github.py --url https://github.com/<owner>/<repo>/tree/<ref>/<path>`
|
||||
- Example (experimental skill): `scripts/install-skill-from-github.py --repo openai/skills --path skills/.experimental/<skill-name>`
|
||||
|
||||
## Behavior and Options
|
||||
|
||||
- Defaults to direct download for public GitHub repos.
|
||||
- If download fails with auth/permission errors, falls back to git sparse checkout.
|
||||
- Aborts if the destination skill directory already exists.
|
||||
- Installs into `$CODEX_HOME/skills/<skill-name>` (defaults to `~/.codex/skills`).
|
||||
- Multiple `--path` values install multiple skills in one run, each named from the path basename unless `--name` is supplied.
|
||||
- Options: `--ref <ref>` (default `main`), `--dest <path>`, `--method auto|download|git`.
|
||||
|
||||
## Notes
|
||||
|
||||
- Curated listing is fetched from `https://github.com/openai/skills/tree/main/skills/.curated` via the GitHub API. If it is unavailable, explain the error and exit.
|
||||
- Private GitHub repos can be accessed via existing git credentials or optional `GITHUB_TOKEN`/`GH_TOKEN` for download.
|
||||
- Git fallback tries HTTPS first, then SSH.
|
||||
- The skills at https://github.com/openai/skills/tree/main/skills/.system are preinstalled, so no need to help users install those. If they ask, just explain this. If they insist, you can download and overwrite.
|
||||
- Installed annotations come from `$CODEX_HOME/skills`.
|
||||
@@ -0,0 +1,5 @@
|
||||
interface:
|
||||
display_name: "Skill Installer"
|
||||
short_description: "Install curated skills from openai/skills or other repos"
|
||||
icon_small: "./assets/skill-installer-small.svg"
|
||||
icon_large: "./assets/skill-installer.png"
|
||||
@@ -0,0 +1,3 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
|
||||
<path fill="#0D0D0D" d="M2.145 3.959a2.033 2.033 0 0 1 2.022-1.824h5.966c.551 0 .997 0 1.357.029.367.03.692.093.993.246l.174.098c.397.243.72.593.932 1.01l.053.114c.116.269.168.557.194.878.03.36.03.805.03 1.357v4.3a2.365 2.365 0 0 1-2.366 2.365h-1.312a2.198 2.198 0 0 1-4.377 0H4.167A2.032 2.032 0 0 1 2.135 10.5V9.333l.004-.088A.865.865 0 0 1 3 8.468l.116-.006A1.135 1.135 0 0 0 3 6.199a.865.865 0 0 1-.865-.864V4.167l.01-.208Zm1.054 1.186a2.198 2.198 0 0 1 0 4.376v.98c0 .534.433.967.968.967H6l.089.004a.866.866 0 0 1 .776.861 1.135 1.135 0 0 0 2.27 0c0-.478.387-.865.865-.865h1.5c.719 0 1.301-.583 1.301-1.301v-4.3c0-.57 0-.964-.025-1.27a1.933 1.933 0 0 0-.09-.493L12.642 4a1.47 1.47 0 0 0-.541-.585l-.102-.056c-.126-.065-.295-.11-.596-.135a17.31 17.31 0 0 0-1.27-.025H4.167a.968.968 0 0 0-.968.968v.978Z"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 923 B |
Binary file not shown.
|
After Width: | Height: | Size: 1.1 KiB |
@@ -0,0 +1,21 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Shared GitHub helpers for skill install scripts."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
import urllib.request
|
||||
|
||||
|
||||
def github_request(url: str, user_agent: str) -> bytes:
|
||||
headers = {"User-Agent": user_agent}
|
||||
token = os.environ.get("GITHUB_TOKEN") or os.environ.get("GH_TOKEN")
|
||||
if token:
|
||||
headers["Authorization"] = f"token {token}"
|
||||
req = urllib.request.Request(url, headers=headers)
|
||||
with urllib.request.urlopen(req) as resp:
|
||||
return resp.read()
|
||||
|
||||
|
||||
def github_api_contents_url(repo: str, path: str, ref: str) -> str:
|
||||
return f"https://api.github.com/repos/{repo}/contents/{path}?ref={ref}"
|
||||
@@ -0,0 +1,308 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Install a skill from a GitHub repo path into $CODEX_HOME/skills."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
from dataclasses import dataclass
|
||||
import os
|
||||
import shutil
|
||||
import subprocess
|
||||
import sys
|
||||
import tempfile
|
||||
import urllib.error
|
||||
import urllib.parse
|
||||
import zipfile
|
||||
|
||||
from github_utils import github_request
|
||||
DEFAULT_REF = "main"
|
||||
|
||||
|
||||
@dataclass
|
||||
class Args:
|
||||
url: str | None = None
|
||||
repo: str | None = None
|
||||
path: list[str] | None = None
|
||||
ref: str = DEFAULT_REF
|
||||
dest: str | None = None
|
||||
name: str | None = None
|
||||
method: str = "auto"
|
||||
|
||||
|
||||
@dataclass
|
||||
class Source:
|
||||
owner: str
|
||||
repo: str
|
||||
ref: str
|
||||
paths: list[str]
|
||||
repo_url: str | None = None
|
||||
|
||||
|
||||
class InstallError(Exception):
|
||||
pass
|
||||
|
||||
|
||||
def _codex_home() -> str:
|
||||
return os.environ.get("CODEX_HOME", os.path.expanduser("~/.codex"))
|
||||
|
||||
|
||||
def _tmp_root() -> str:
|
||||
base = os.path.join(tempfile.gettempdir(), "codex")
|
||||
os.makedirs(base, exist_ok=True)
|
||||
return base
|
||||
|
||||
|
||||
def _request(url: str) -> bytes:
|
||||
return github_request(url, "codex-skill-install")
|
||||
|
||||
|
||||
def _parse_github_url(url: str, default_ref: str) -> tuple[str, str, str, str | None]:
|
||||
parsed = urllib.parse.urlparse(url)
|
||||
if parsed.netloc != "github.com":
|
||||
raise InstallError("Only GitHub URLs are supported for download mode.")
|
||||
parts = [p for p in parsed.path.split("/") if p]
|
||||
if len(parts) < 2:
|
||||
raise InstallError("Invalid GitHub URL.")
|
||||
owner, repo = parts[0], parts[1]
|
||||
ref = default_ref
|
||||
subpath = ""
|
||||
if len(parts) > 2:
|
||||
if parts[2] in ("tree", "blob"):
|
||||
if len(parts) < 4:
|
||||
raise InstallError("GitHub URL missing ref or path.")
|
||||
ref = parts[3]
|
||||
subpath = "/".join(parts[4:])
|
||||
else:
|
||||
subpath = "/".join(parts[2:])
|
||||
return owner, repo, ref, subpath or None
|
||||
|
||||
|
||||
def _download_repo_zip(owner: str, repo: str, ref: str, dest_dir: str) -> str:
|
||||
zip_url = f"https://codeload.github.com/{owner}/{repo}/zip/{ref}"
|
||||
zip_path = os.path.join(dest_dir, "repo.zip")
|
||||
try:
|
||||
payload = _request(zip_url)
|
||||
except urllib.error.HTTPError as exc:
|
||||
raise InstallError(f"Download failed: HTTP {exc.code}") from exc
|
||||
with open(zip_path, "wb") as file_handle:
|
||||
file_handle.write(payload)
|
||||
with zipfile.ZipFile(zip_path, "r") as zip_file:
|
||||
_safe_extract_zip(zip_file, dest_dir)
|
||||
top_levels = {name.split("/")[0] for name in zip_file.namelist() if name}
|
||||
if not top_levels:
|
||||
raise InstallError("Downloaded archive was empty.")
|
||||
if len(top_levels) != 1:
|
||||
raise InstallError("Unexpected archive layout.")
|
||||
return os.path.join(dest_dir, next(iter(top_levels)))
|
||||
|
||||
|
||||
def _run_git(args: list[str]) -> None:
|
||||
result = subprocess.run(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
|
||||
if result.returncode != 0:
|
||||
raise InstallError(result.stderr.strip() or "Git command failed.")
|
||||
|
||||
|
||||
def _safe_extract_zip(zip_file: zipfile.ZipFile, dest_dir: str) -> None:
|
||||
dest_root = os.path.realpath(dest_dir)
|
||||
for info in zip_file.infolist():
|
||||
extracted_path = os.path.realpath(os.path.join(dest_dir, info.filename))
|
||||
if extracted_path == dest_root or extracted_path.startswith(dest_root + os.sep):
|
||||
continue
|
||||
raise InstallError("Archive contains files outside the destination.")
|
||||
zip_file.extractall(dest_dir)
|
||||
|
||||
|
||||
def _validate_relative_path(path: str) -> None:
|
||||
if os.path.isabs(path) or os.path.normpath(path).startswith(".."):
|
||||
raise InstallError("Skill path must be a relative path inside the repo.")
|
||||
|
||||
|
||||
def _validate_skill_name(name: str) -> None:
|
||||
altsep = os.path.altsep
|
||||
if not name or os.path.sep in name or (altsep and altsep in name):
|
||||
raise InstallError("Skill name must be a single path segment.")
|
||||
if name in (".", ".."):
|
||||
raise InstallError("Invalid skill name.")
|
||||
|
||||
|
||||
def _git_sparse_checkout(repo_url: str, ref: str, paths: list[str], dest_dir: str) -> str:
|
||||
repo_dir = os.path.join(dest_dir, "repo")
|
||||
clone_cmd = [
|
||||
"git",
|
||||
"clone",
|
||||
"--filter=blob:none",
|
||||
"--depth",
|
||||
"1",
|
||||
"--sparse",
|
||||
"--single-branch",
|
||||
"--branch",
|
||||
ref,
|
||||
repo_url,
|
||||
repo_dir,
|
||||
]
|
||||
try:
|
||||
_run_git(clone_cmd)
|
||||
except InstallError:
|
||||
_run_git(
|
||||
[
|
||||
"git",
|
||||
"clone",
|
||||
"--filter=blob:none",
|
||||
"--depth",
|
||||
"1",
|
||||
"--sparse",
|
||||
"--single-branch",
|
||||
repo_url,
|
||||
repo_dir,
|
||||
]
|
||||
)
|
||||
_run_git(["git", "-C", repo_dir, "sparse-checkout", "set", *paths])
|
||||
_run_git(["git", "-C", repo_dir, "checkout", ref])
|
||||
return repo_dir
|
||||
|
||||
|
||||
def _validate_skill(path: str) -> None:
|
||||
if not os.path.isdir(path):
|
||||
raise InstallError(f"Skill path not found: {path}")
|
||||
skill_md = os.path.join(path, "SKILL.md")
|
||||
if not os.path.isfile(skill_md):
|
||||
raise InstallError("SKILL.md not found in selected skill directory.")
|
||||
|
||||
|
||||
def _copy_skill(src: str, dest_dir: str) -> None:
|
||||
os.makedirs(os.path.dirname(dest_dir), exist_ok=True)
|
||||
if os.path.exists(dest_dir):
|
||||
raise InstallError(f"Destination already exists: {dest_dir}")
|
||||
shutil.copytree(src, dest_dir)
|
||||
|
||||
|
||||
def _build_repo_url(owner: str, repo: str) -> str:
|
||||
return f"https://github.com/{owner}/{repo}.git"
|
||||
|
||||
|
||||
def _build_repo_ssh(owner: str, repo: str) -> str:
|
||||
return f"git@github.com:{owner}/{repo}.git"
|
||||
|
||||
|
||||
def _prepare_repo(source: Source, method: str, tmp_dir: str) -> str:
|
||||
if method in ("download", "auto"):
|
||||
try:
|
||||
return _download_repo_zip(source.owner, source.repo, source.ref, tmp_dir)
|
||||
except InstallError as exc:
|
||||
if method == "download":
|
||||
raise
|
||||
err_msg = str(exc)
|
||||
if "HTTP 401" in err_msg or "HTTP 403" in err_msg or "HTTP 404" in err_msg:
|
||||
pass
|
||||
else:
|
||||
raise
|
||||
if method in ("git", "auto"):
|
||||
repo_url = source.repo_url or _build_repo_url(source.owner, source.repo)
|
||||
try:
|
||||
return _git_sparse_checkout(repo_url, source.ref, source.paths, tmp_dir)
|
||||
except InstallError:
|
||||
repo_url = _build_repo_ssh(source.owner, source.repo)
|
||||
return _git_sparse_checkout(repo_url, source.ref, source.paths, tmp_dir)
|
||||
raise InstallError("Unsupported method.")
|
||||
|
||||
|
||||
def _resolve_source(args: Args) -> Source:
|
||||
if args.url:
|
||||
owner, repo, ref, url_path = _parse_github_url(args.url, args.ref)
|
||||
if args.path is not None:
|
||||
paths = list(args.path)
|
||||
elif url_path:
|
||||
paths = [url_path]
|
||||
else:
|
||||
paths = []
|
||||
if not paths:
|
||||
raise InstallError("Missing --path for GitHub URL.")
|
||||
return Source(owner=owner, repo=repo, ref=ref, paths=paths)
|
||||
|
||||
if not args.repo:
|
||||
raise InstallError("Provide --repo or --url.")
|
||||
if "://" in args.repo:
|
||||
return _resolve_source(
|
||||
Args(url=args.repo, repo=None, path=args.path, ref=args.ref)
|
||||
)
|
||||
|
||||
repo_parts = [p for p in args.repo.split("/") if p]
|
||||
if len(repo_parts) != 2:
|
||||
raise InstallError("--repo must be in owner/repo format.")
|
||||
if not args.path:
|
||||
raise InstallError("Missing --path for --repo.")
|
||||
paths = list(args.path)
|
||||
return Source(
|
||||
owner=repo_parts[0],
|
||||
repo=repo_parts[1],
|
||||
ref=args.ref,
|
||||
paths=paths,
|
||||
)
|
||||
|
||||
|
||||
def _default_dest() -> str:
|
||||
return os.path.join(_codex_home(), "skills")
|
||||
|
||||
|
||||
def _parse_args(argv: list[str]) -> Args:
|
||||
parser = argparse.ArgumentParser(description="Install a skill from GitHub.")
|
||||
parser.add_argument("--repo", help="owner/repo")
|
||||
parser.add_argument("--url", help="https://github.com/owner/repo[/tree/ref/path]")
|
||||
parser.add_argument(
|
||||
"--path",
|
||||
nargs="+",
|
||||
help="Path(s) to skill(s) inside repo",
|
||||
)
|
||||
parser.add_argument("--ref", default=DEFAULT_REF)
|
||||
parser.add_argument("--dest", help="Destination skills directory")
|
||||
parser.add_argument(
|
||||
"--name", help="Destination skill name (defaults to basename of path)"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--method",
|
||||
choices=["auto", "download", "git"],
|
||||
default="auto",
|
||||
)
|
||||
return parser.parse_args(argv, namespace=Args())
|
||||
|
||||
|
||||
def main(argv: list[str]) -> int:
|
||||
args = _parse_args(argv)
|
||||
try:
|
||||
source = _resolve_source(args)
|
||||
source.ref = source.ref or args.ref
|
||||
if not source.paths:
|
||||
raise InstallError("No skill paths provided.")
|
||||
for path in source.paths:
|
||||
_validate_relative_path(path)
|
||||
dest_root = args.dest or _default_dest()
|
||||
tmp_dir = tempfile.mkdtemp(prefix="skill-install-", dir=_tmp_root())
|
||||
try:
|
||||
repo_root = _prepare_repo(source, args.method, tmp_dir)
|
||||
installed = []
|
||||
for path in source.paths:
|
||||
skill_name = args.name if len(source.paths) == 1 else None
|
||||
skill_name = skill_name or os.path.basename(path.rstrip("/"))
|
||||
_validate_skill_name(skill_name)
|
||||
if not skill_name:
|
||||
raise InstallError("Unable to derive skill name.")
|
||||
dest_dir = os.path.join(dest_root, skill_name)
|
||||
if os.path.exists(dest_dir):
|
||||
raise InstallError(f"Destination already exists: {dest_dir}")
|
||||
skill_src = os.path.join(repo_root, path)
|
||||
_validate_skill(skill_src)
|
||||
_copy_skill(skill_src, dest_dir)
|
||||
installed.append((skill_name, dest_dir))
|
||||
finally:
|
||||
if os.path.isdir(tmp_dir):
|
||||
shutil.rmtree(tmp_dir, ignore_errors=True)
|
||||
for skill_name, dest_dir in installed:
|
||||
print(f"Installed {skill_name} to {dest_dir}")
|
||||
return 0
|
||||
except InstallError as exc:
|
||||
print(f"Error: {exc}", file=sys.stderr)
|
||||
return 1
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main(sys.argv[1:]))
|
||||
107
.agents/skills/.system/skill-installer/scripts/list-skills.py
Normal file
107
.agents/skills/.system/skill-installer/scripts/list-skills.py
Normal file
@@ -0,0 +1,107 @@
|
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#!/usr/bin/env python3
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"""List skills from a GitHub repo path."""
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from __future__ import annotations
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import argparse
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import json
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import os
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import sys
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import urllib.error
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from github_utils import github_api_contents_url, github_request
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DEFAULT_REPO = "openai/skills"
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DEFAULT_PATH = "skills/.curated"
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DEFAULT_REF = "main"
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class ListError(Exception):
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pass
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class Args(argparse.Namespace):
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repo: str
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path: str
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ref: str
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format: str
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def _request(url: str) -> bytes:
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return github_request(url, "codex-skill-list")
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def _codex_home() -> str:
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return os.environ.get("CODEX_HOME", os.path.expanduser("~/.codex"))
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def _installed_skills() -> set[str]:
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root = os.path.join(_codex_home(), "skills")
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if not os.path.isdir(root):
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return set()
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entries = set()
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for name in os.listdir(root):
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path = os.path.join(root, name)
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if os.path.isdir(path):
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entries.add(name)
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return entries
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def _list_skills(repo: str, path: str, ref: str) -> list[str]:
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api_url = github_api_contents_url(repo, path, ref)
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try:
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payload = _request(api_url)
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except urllib.error.HTTPError as exc:
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if exc.code == 404:
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raise ListError(
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"Skills path not found: "
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f"https://github.com/{repo}/tree/{ref}/{path}"
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) from exc
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raise ListError(f"Failed to fetch skills: HTTP {exc.code}") from exc
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data = json.loads(payload.decode("utf-8"))
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if not isinstance(data, list):
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raise ListError("Unexpected skills listing response.")
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skills = [item["name"] for item in data if item.get("type") == "dir"]
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return sorted(skills)
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def _parse_args(argv: list[str]) -> Args:
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parser = argparse.ArgumentParser(description="List skills.")
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parser.add_argument("--repo", default=DEFAULT_REPO)
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parser.add_argument(
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"--path",
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default=DEFAULT_PATH,
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help="Repo path to list (default: skills/.curated)",
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)
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parser.add_argument("--ref", default=DEFAULT_REF)
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parser.add_argument(
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"--format",
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choices=["text", "json"],
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default="text",
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help="Output format",
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)
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return parser.parse_args(argv, namespace=Args())
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def main(argv: list[str]) -> int:
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args = _parse_args(argv)
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try:
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skills = _list_skills(args.repo, args.path, args.ref)
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installed = _installed_skills()
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if args.format == "json":
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payload = [
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{"name": name, "installed": name in installed} for name in skills
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]
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print(json.dumps(payload))
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else:
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for idx, name in enumerate(skills, start=1):
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suffix = " (already installed)" if name in installed else ""
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print(f"{idx}. {name}{suffix}")
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return 0
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except ListError as exc:
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print(f"Error: {exc}", file=sys.stderr)
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return 1
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if __name__ == "__main__":
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raise SystemExit(main(sys.argv[1:]))
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Block a user