OpenAI Agents SDK is a Python framework for building workflows in which multiple AI agents use tools, delegate tasks, follow safety checks, and involve people when needed. Developers use it to create and monitor agent, sandbox, realtime, and voice applications.
Borrowing it
Nothing to install: this file belongs to openai/openai-agents-python. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/openai/openai-agents-python/main/.agents/skills/docs-sync/SKILL.mdgit clone --depth 1 https://github.com/openai/openai-agents-pythonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/openai/openai-agents-python/docs-sync)<a href="https://agentmods.dev/skills/openai/openai-agents-python/docs-sync"><img src="https://agentmods.dev/badge/skills/openai/openai-agents-python/docs-sync/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/openai/openai-agents-python/docs-sync"><img src="https://agentmods.dev/badge/skills/openai/openai-agents-python/docs-sync.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.01048 |
| Opus 5.5 | $0.00006 | $0.00419 |
| Sonnet 5.5 | $0.00003 | $0.00210 |
| Haiku 4.5 | $0.00002 | $0.00105 |
Grade A, and why
docs-sync scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Docs Sync
Overview
Identify doc coverage gaps and inaccuracies by comparing main branch features and configuration options against the current docs structure, then propose targeted improvements.
Authorization and scope
For an audit or proposal-only request, report findings without editing. When the user requests updates or has already approved a plan, complete those local edits and applicable checks without asking again. Ask only about unresolved scope, behavior, release timing, or additional authority. Keep generated translations untouched. Apply the repository's Documentation Release Timing policy before including unreleased behavior in docs/.
Workflow
-
Confirm scope and base branch
- Identify the current branch and default branch (usually
main). - Prefer analyzing the current branch to keep work aligned with in-flight changes.
- Use a branch diff only for a branch-scoped request. A requested topic or released-doc correction remains in scope even when it is unrelated to the current branch diff.
- Avoid switching branches if it would disrupt local changes. Prefer read-only inspection such as
git show main:<path>. If a separate checkout is genuinely required, stop and obtain the explicit approval required byAGENTS.mdbefore creating or switching a worktree.
- Identify the current branch and default branch (usually
-
Build a feature inventory from the selected scope
- Bound the inventory to the requested topic or diff. Inventory the full surface only for an explicitly comprehensive audit.
- For branch-scoped work, inspect feature additions, changes, and removals relative to the intended base.
- Focus on user-facing behavior: public exports, configuration options, environment variables, CLI commands, default values, and documented runtime behaviors.
- Capture evidence for each item (file path + symbol/setting).
- Use targeted search to find option types and feature flags (for example:
rg "Settings",rg "Config",rg "os.environ",rg "OPENAI_"). - When the topic involves OpenAI platform features, invoke
$openai-knowledgeto pull current details from the OpenAI Developer Docs MCP server instead of guessing, while treating the SDK source code as the source of truth when discrepancies appear.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · +4 lines · -64 tokens per session e5989e548a13
- 1mo ago First seen · 78 lines · 79 tokens per session scan A 5c50f9853843
docs-sync is a skill published in the GitHub repository openai/openai-agents-python (30,339 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 1,048 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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