Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/openai/openai-agents-python/openai-knowledgenpx skills add openai/openai-agents-python --skill openai-knowledgegit clone --depth 1 https://github.com/openai/openai-agents-pythonWhat 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 | $0.00083 | $0.00464 |
| Opus 5 | $0.00042 | $0.00232 |
| Sonnet 5 | $0.00017 | $0.00093 |
| Haiku 4.5 | $0.00008 | $0.00046 |
Grade B, and why
openai-knowledge scanned grade B with 1 finding 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 2d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
- Config file (`~/.codex/config.toml`): Copies of this mod
1 near-identical copy found in the catalogue:
- openai-knowledge — 100% identical, 0 lines differ
What it actually says
OpenAI Knowledge
Overview
Use the OpenAI Developer Documentation MCP server to search and fetch exact docs (markdown), then base your answer on that text instead of guessing.
Workflow
1) Check whether the Docs MCP server is available
If the mcp__openaiDeveloperDocs__* tools are available, use them.
If you are unsure, run codex mcp list and check for openaiDeveloperDocs.
2) Use MCP tools to pull exact docs
- Search first, then fetch the specific page or pages.
mcp__openaiDeveloperDocs__search_openai_docs→ pick the best URL.mcp__openaiDeveloperDocs__fetch_openai_doc→ retrieve the exact markdown (optionally with ananchor).
- When you need endpoint schemas or parameters, use:
mcp__openaiDeveloperDocs__get_openapi_specmcp__openaiDeveloperDocs__list_api_endpoints
Base your answer on the fetched text and quote or paraphrase it precisely. Do not invent flags, field names, defaults, or limits.
3) If MCP is not configured, guide setup (do not change config unless asked)
Provide one of these setup options, then ask the user to restart the Codex session so the tools load:
- CLI:
codex mcp add openaiDeveloperDocs --url https://developers.openai.com/mcp
- Config file (
~/.codex/config.toml):- Add:
[mcp_servers.openaiDeveloperDocs] url = "https://developers.openai.com/mcp"
- Add:
Also point to: https://developers.openai.com/resources/docs-mcp#quickstart
What ships with it
1 file 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.
- 2d ago First seen · 45 lines · 83 tokens per session scan B 13cd63da9145
openai-knowledge is a skill published in the GitHub repository openai/openai-agents-python (29,075 stars, last pushed 4d ago), licensed MIT. It adds 83 tokens to every session and 464 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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