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/ghabix/spinecodex/openai-docsnpx skills add GhabiX/SpineCodex --skill openai-docsgit clone --depth 1 https://github.com/GhabiX/SpineCodexWhat 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 | $0.00113 | $0.01103 |
| Opus 5 | $0.00056 | $0.00551 |
| Sonnet 5 | $0.00023 | $0.00221 |
| Haiku 4.5 | $0.00011 | $0.00110 |
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 3d 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.
This is a copy
100% identical to openai-docs — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenAI Docs
Provide current, cited OpenAI product, API, model, and Codex guidance. Read zero or one primary reference.
First substantive action: Search the user's exact requested official OpenAI documentation topic and any explicitly named model using a concise, topic-specific query of 2-6 essential terms. When an already-available direct official documentation search and page-retrieval capability is present, use it first: search, then fetch or open the matching official page before general web search. Otherwise, immediately use official-domain web search, then actually open or fetch the relevant official page. Complete this source order before reading a reference, inspecting local or repository files, running a Codex manual or model resolver, drafting a plan, or answering from memory. Use the actual fetched page, not a search snippet or an unopened link. If one official search or page does not establish the answer, search another appropriate official domain and actually open or fetch the result. Preserve the exact requested model; never substitute a newer model.
Only exception: An explicitly requested, genuinely broad, cross-topic Codex setup, orientation, or system-map synthesis may use the manual first when shell execution and an allowed temporary cache are available. A specific Codex feature, setting, command, error, model, or requested citation remains docs-first. Mixed Chat/Work/Codex comparisons are official documentation questions, not manual-first Codex requests.
For generic software tasks, answer the software task directly. OpenAI implementation, debugging, SDK, API, prompting, agent, and eval requests are not generic.
For a straightforward factual or citation-only request, follow the source order and do not read a route reference. This includes straightforward API facts, ChatGPT Work or mixed Chat/Work/Codex comparisons, model tiers, aliases, Pro mode, reasoning settings, factual migration baselines, and narrow Codex facts. Prioritize learn.chatgpt.com for ChatGPT Work.
What ships with it
16 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.
- agents/openai.yaml 370 B
- assets/openai-small.svg 1.1 KB
- assets/openai.png 1.4 KB
- LICENSE.txt 11 KB
- references/codex-self-knowledge.md 7.2 KB
- references/latest-model.md 2.0 KB
- references/mcp-diagnostics.md 2.3 KB
- references/model-migration.md 4.9 KB
- references/model-selection.md 1.3 KB
- references/official-docs.md 3.3 KB
- references/prompting-guide.md 15 KB
- references/upgrade-guide.md 1.0 KB
- references/upgrading-to-gpt-5p6-sol.md 23 KB
- scripts/fetch-codex-manual.mjs 16 KB runs code
- scripts/resolve-latest-model-info 1.0 KB
- scripts/resolve-latest-model-info.cjs 3.8 KB runs code
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.
- 3d ago First seen · 39 lines · 113 tokens per session scan A 7cb8fa1b2a0c
openai-docs is a skill published in the GitHub repository GhabiX/SpineCodex (126 stars, last pushed 7d ago), licensed Apache-2.0. It adds 113 tokens to every session and 1,103 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to openai-docs, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
apm-usage
Activate when the user asks about APM (Agent Package Manager): installing, configuring, authoring, or troubleshooting AI-agent packages, dependencies, compilation, MCP servers, policy, or any apm CLI command.
clean-user-facing-text
Audit and finalize authorized natural-language text meant for readers: strip suspicious invisible Unicode, then rewrite prose while keeping facts, meaning, and the writer's voice. Use when the user asks to clean, humanize, polish, or finalize articles, manuscripts, reports, documentation, emails, product copy, UI…
sessions
Search and ask questions about coding agent session history across Claude Code, Codex, and Cursor. Use when asking what was worked on, what was tried before, how a problem was investigated across sessions, what happened recently, or any question about past agent sessions. Also use when the user references prior…
codex-autoresearch
Run autonomous, measurable experiments in a Git repository: change one hypothesis, verify a numeric metric, keep improvements, and revert failures. Use when the user wants Codex to keep iterating toward a numeric target in the foreground or as a detached background run. Do not use for ordinary one-shot coding…
map-review
Interactive 4-section code review using monitor, predictor, and evaluator agents plus the user and maintainer role reviewers on current changes. Use when reviewing a diff, PR, or staged work before merge. Do NOT use to plan or implement; use map-plan or map-efficient.
map-wayfind
Decision-frontier wayfinding: build and work a durable map of open design decisions BEFORE planning, for large or foggy efforts where /map-plan would force premature decomposition. Use when a task is too big or too vague to decompose — many unknowns, tangled decisions, or "I'm not even sure what to build yet" — and…