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/haohao-end/openagent/openai-docsnpx skills add Haohao-end/openagent --skill openai-docsgit clone --depth 1 https://github.com/Haohao-end/openagentWrote 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/haohao-end/openagent/openai-docs)<a href="https://agentmods.dev/skills/haohao-end/openagent/openai-docs"><img src="https://agentmods.dev/badge/skills/haohao-end/openagent/openai-docs.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00074 | $0.01445 |
| Opus 5 | $0.00037 | $0.00723 |
| Sonnet 5 | $0.00015 | $0.00289 |
| Haiku 4.5 | $0.00007 | $0.00145 |
Grade A, and why
openai-docs 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 7d 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- openai-docs — 100% identical, 0 lines differ
- openai-docs — 100% identical, 0 lines differ
- openai-docs — 89% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 also owns model selection, API model migration, and prompt-upgrade guidance. 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_docsto find the most relevant doc pages. - Use
mcp__openaiDeveloperDocs__fetch_openai_docto pull exact sections and quote/paraphrase accurately. - Use
mcp__openaiDeveloperDocs__list_openai_docsonly when you need to browse or discover pages without a clear query. - For model-selection, "latest model", or default-model questions, fetch
https://developers.openai.com/api/docs/guides/latest-model.mdfirst. If that is unavailable, loadreferences/latest-model.md. - For model upgrades or prompt upgrades, run
node scripts/resolve-latest-model-info.jsonly when the target is latest/current/default or otherwise unspecified; otherwise preserve the explicitly requested target. - Preserve explicit target requests: if the user names a target model like "migrate to GPT-5.4", keep that requested target even if
latest-model.mdnames a newer model. Mention newer guidance only as optional. - If current remote guidance is needed, fetch both the returned migration and prompting guide URLs directly. If direct fetch fails, use MCP/search fallback; if that also fails, use bundled fallback references and disclose the fallback.
OpenAI product snapshots
- Apps SDK: Build ChatGPT apps by providing a web component UI and an MCP server that exposes your app's tools to ChatGPT.
- Responses API: A unified endpoint designed for stateful, multimodal, tool-using interactions in agentic workflows.
- Chat Completions API: Generate a model response from a list of messages comprising a conversation.
- Codex: OpenAI's coding agent for software development that can write, understand, review, and debug code.
- gpt-oss: Open-weight OpenAI reasoning models (gpt-oss-120b and gpt-oss-20b) released under the Apache 2.0 license.
- Realtime API: Build low-latency, multimodal experiences including natural speech-to-speech conversations.
- 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.
What ships with it
7 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.
- 7d ago First seen · 83 lines · 74 tokens per session scan A 1941a2fa1d81
openai-docs is a skill published in the GitHub repository Haohao-end/openagent (805 stars, last pushed 1mo ago), licensed MIT. It adds 74 tokens to every session and 1,445 once invoked, about $0.0004 per session on Opus 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.
Other skills, from other repositories
resources
Prompt Guide LLM Settings: https://www.promptingguide.ai/introduction/settings Prompt Design: https://www.promptingguide.ai/introduction/elements.
html-ppt-hermes-cyber-terminal
Open Design + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
llm-redteam-overview
LLM red team category — full AATMF v3 tactic coverage (T01–T15). Routing skill: read this first to identify which tactic applies, then load the matching sub-skill. Maps to MITRE ATLAS where overlap exists.
omh-llm-app-dev
This is a Hermes-native llm-app-dev workflow skill.
omh-model-setup
This is a Hermes-native model-setup workflow skill.
omh-model-optimization
This is a Hermes-native model-optimization workflow skill.