Agent skill

Docs Guide

by fivetaku in fivetaku/gptaku-plugins-codex

Fetch and explain official documentation for any library, framework, API, or service using an llms.txt-first strategy — triggers on "How do I…", "What is…", "How does X work", "Best practice for…"…

MITAuto-check passedBackend & APIs

Install Docs Guide

skills CLI
$ npx skills add fivetaku/gptaku-plugins-codex --skill docs-guide -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install fivetaku/gptaku-plugins-codex docs-guide --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/fivetaku/gptaku-plugins-codex.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/docs-guide-codex/skills/docs-guide .claude/skills/docs-guide && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
docs-guide
GitHub stars
128
Token cost
~3.5k tokens
SKILL.md length
1,632 words
Files
6 (incl. references)
Skills in repo
25
Repo updated
First seen
Licence
MIT

At a glance

Fetch and explain official documentation for any library, framework, API, or service using an llms.txt-first strategy — triggers on "How do I…", "What is…", "How does X work", "Best practice for…"…

  • How does X work
  • SKILL.md covers Scope, Arguments, Clarification — docs-guide is… and Step 0 — Project Context…, plus 7 more sections
  • Reaches raw.githubusercontent.com
  • Best practice for… about React

What it does

Docs Guide is an agent skill from fivetaku/gptaku-plugins-codex. Fetch and explain official documentation for any library, framework, API, or service using an llms.txt-first strategy — triggers on "How do I…", "What is…", "How does X work", "Best practice for…" about React, Next.js, Vue, Django, FastAPI, Stripe, Supabase, LangChain and any other library; on explicit doc requests ("공식 문서", "official docs", "문서 기반으로", "docs에서 확인해줘", "React 공식 문서 찾아줘", "fetch the Next.js docs", "공식 문서 URL 알려줘"); on version-specific or spec-level queries (latest model ID, pricing, deprecation…

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/fallback-strategies.md`, `references/knowledge-base.md` and `references/llms-txt-sites.md`).

It sits in Backend & APIs, covering AI search optimization, Backend development and Building AI agents. It works with Next.js, React, FastAPI and Stripe. The repository describes itself as: Codex-native GPTaku plugin marketplace. The licence is MIT.

When your agent uses it

  • How does X work
  • Best practice for… about React
  • LangChain and any other library
  • On explicit doc requests (공식 문서

Example prompts

  • “How do I…”
  • “What is…”
  • “How does X work”
  • “/docs-guide”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit d3b47fc. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • raw.githubusercontent.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Docs Guide loads about 3.5k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 167 tokens; SKILL.md has 1,632 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~167
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~11k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from fivetaku/gptaku-plugins-codex at commit d3b47fc, republished under its MIT licence (© fivetaku). 1,632 words, ~3,454 tokens.

Download SKILL.mdSave it as .claude/skills/docs-guide/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
docs-guide
description
Fetch and explain official documentation for any library, framework, API, or service using an llms.txt-first strategy — triggers on "How do I…", "What is…", "How does X work", "Best practice for…" about React, Next.js, Vue, Django, FastAPI, Stripe, Supabase, LangChain and any other library; on explicit doc requests ("공식 문서", "official docs", "문서 기반으로", "docs에서 확인해줘", "React 공식 문서 찾아줘", "fetch the Next.js docs", "공식 문서 URL 알려줘"); on version-specific or spec-level queries (latest model ID, pricing, deprecation, context window); and on questions about the llms.txt standard itself ("llms.txt란 뭐야", "which sites have llms.txt", "documentation for LLMs").

docs-guide for Codex

Read these first:

  • references/llms-txt-sites.md
  • references/fallback-strategies.md

Load on demand (spec-level or fetch-prompt workflow questions):

  • references/webfetch-prompts.md
  • references/regression-cases.md

Scope

Any library, framework, API, or service with official documentation — including LLM provider APIs (OpenAI, Anthropic, Google Gemini, etc.) via their llms.txt indexes listed in references/llms-txt-sites.md.

Trigger on:

  • "How do I…", "What is…", "How does X work", "Best practice for…" about any library or framework
  • Explicit doc requests — "공식문서", "official docs", "문서 기반으로", "docs에서 확인해줘"
  • Version-sensitive or spec-level questions about external libraries
  • Questions about the llms.txt standard itself (what it is, which sites have it, llms.txt vs llms-full.txt)

When a question spans several tools or skills (e.g., "How to use Stripe inside my agent runtime"), this skill owns the external-documentation part only.


Arguments

When invoked as docs-guide [library] [question], parse the leading token(s) as the library and the rest as the topic:

  • docs-guide react useEffect → Library: React, Question: useEffect
  • docs-guide next.js app router caching → Library: Next.js, Question: app router caching
  • docs-guide fastapi dependency injection → Library: FastAPI, Question: dependency injection
  • docs-guide (no args) → ask which library/framework and which topic (one §A question covering both), unless Step 0 project context makes the library obvious

Clarification — docs-guide is minimal-interview

This plugin mostly needs just two facts: library and topic.

Per shared/questioning-policy.md §2c — if the user already named the library and topic, proceed immediately without asking anything.

If the library OR topic is genuinely ambiguous (e.g., "Router" with no project context), ask exactly ONE numbered-option question per §A below, then proceed.

§A — Numbered-option format (Codex CLI has no multiple-choice card UI)

Codex CLI has no card UI. When you must ask, output a chat block:

질문: <한 줄 질문>
1. <추천안> — 무엇인지, 왜 이걸 추천하는지
2. <대안> — 무엇인지, 트레이드오프
3. 직접 입력 (문장으로 말씀해 주세요)
  • Recommended option always goes first (1번).
  • Multi-pick → "여러 개면 1,3처럼 적어주세요."
  • Never ask more than once; if still unclear, proceed with the most likely interpretation.

Step 0 — Project Context Detection

Before fetching, quickly scan local dependency files to detect library version:

package.json, requirements.txt, pyproject.toml, go.mod, Cargo.toml, pom.xml, build.gradle

Use this for:

  • Version detection: "react": "^19.0.0" → fetch React 19 docs
  • Disambiguation: project has both react-router-dom and express, user asks "Router" → resolve silently
  • Skip unnecessary search: if the library is not installed in the project, say so briefly

Skip this step if the question already names a specific library and version.


Intent Classification (Smart Broad)

FETCH (external lookup needed)
  • Library/framework APIs, configuration, features
  • Setup/installation, migration guides, breaking changes
  • API reference (endpoints, parameters, return types)
  • Questions where wrong info causes bugs (auth, payments, DB queries)
  • Explicit doc requests
SKIP (answer from knowledge)
  • Basic language syntax (Python for loop, JS array methods)
  • General CS concepts (REST, closures)
  • Architecture discussions not tied to a specific library version
DISAMBIGUATE
  • Generic term maps to multiple libraries ("Router", "ORM", "auth", "store")
  • Check Step 0 first; if still ambiguous, ask one §A question

When unsure between FETCH and SKIP, answer from knowledge first, then offer: "공식 문서도 확인해볼까요?"


Version Awareness

  1. Project context first — check Step 0
  2. User mention — "React 19", "Django 5.0"
  3. Normalize — react 18, React v18, @18, ^18.2.0 → all mean React 18.x
  4. Version-specific URLs — Next.js /docs/14/, Django /en/5.0/, Python /3.12/library/
  5. Default — latest stable; note which version was used

Common pitfalls:

SituationRiskAction
"React" without versionReact 18 vs 19 differ significantlyCheck package.json first
Library has LTS and currentUser may need LTS-specific docsAsk if unclear
Pre-release/canary docsMay contain unstable APIsWarn user
Archived docs (e.g., CRA)Deprecated projectNote it

Documentation Retrieval Strategy

Step 1 — Check known llms.txt sites

Load references/llms-txt-sites.md. If the library is listed, use that URL directly.

Step 2 — Try llms.txt on the official site

If not in the known list:

  1. If you know the official docs domain → try llms.txt directly
  2. If unsure → search for {library name} official site to find the domain
  3. Try in order:
    • {official-site}/llms.txt
    • {official-site}/docs/llms.txt
    • {official-site}/llms-full.txt

If llms.txt exists:

  • Read the index to find relevant page URLs
  • Fetch the specific page(s) for the user's question
  • URL fix: if a linked URL ends in .md but returns 404, retry without .md
Step 3 — Fallback strategies (no llms.txt)

Load references/fallback-strategies.md and try in order:

3a. Per-technology strategy — 40+ technologies with best known URLs

3b. GitHub raw markdown (most reliable for OSS):

  • Search: {library name} documentation site:github.com
  • Try: https://raw.githubusercontent.com/{owner}/{repo}/main/docs/{topic}.md
  • Branch fallback: main → master → version branches (e.g., 8.17)

3c. sitemap.xml (universal fallback):

  • Fetch {official-site}/sitemap.xml
  • Filter for /docs/, /guide/, /reference/ patterns
  • Fetch the most relevant page

3d. Platform-specific signals (low reliability for Hugo — skip straight to sitemap/GitHub there):

  • /search/search_index.json → MkDocs (full page text)
  • /objects.inv → Sphinx
  • <meta name="generator"> → Docusaurus, VitePress

3e. Search (last resort):

  • Search {library name} official documentation {topic}
  • Prefer official domains over tutorials/blogs
  • Tell the user which method was used

Spec-Level Drill-Down Requirement (v1.3.3)

For these question types, fetching only the index/overview page is INSUFFICIENT. You MUST fetch the per-item detail page.

Spec-level triggers
  • "최신 / 현재 / newest / latest" model, version, release
  • Exact API identifiers (model IDs, function names, env var names, parameter names)
  • Pricing, token limits, rate limits, quota, deprecation dates
  • Context window / max tokens / output limit
  • Region availability / preview vs GA / tier availability
  • Endpoint compatibility (Responses API, Chat Completions, Batch, embeddings)
  • Modalities / tool support (vision, audio, structured output, function calling)
  • SDK / package version / migration / breaking changes
  • Request parameter names / response schema fields
  • Default model 변경 / sunset date / release date / "deprecated" / "legacy"
  • Feature support matrix ("X 지원하나?", "Y 가능?")
Drill-down protocol

Load references/webfetch-prompts.md before fetching spec-level pages.

  1. Fetch the index/overview page (llms.txt or root docs)
  2. If the question matches any spec-level trigger above, do NOT stop here
  3. From the index, extract actual href URLs for each relevant item
    • Use Template 1 from references/webfetch-prompts.md
    • Do NOT guess URLs from natural names — *-preview, *-beta, *-canary, *-experimental suffixes are unguessable
  4. Fetch each detail page (claim-type-bounded cap below)
  5. Cite the detail page URL in the answer, not just the index
Show full SKILL.md (683 more words)Show less
Drill-down cap
Question classIndexDetail max
general how-to11-2
spec single target13
latest / current 질문15 (overview + changelog + pricing/deprecation)
matrix / comparisonup to 8 total3 per provider
30+ candidatesrank by exact token/title/href match → top 5-8only those needed for claim

Stop condition: each exact claim in the answer (model ID, price, date, availability, schema) has at least one detail-page source.


Quality Gate

General questions
  • Minimum: at least 1 official URL actually fetched + 1 specific fact or code example from that source
Spec-level questions
  • 1 index/overview URL (proves item exists in current docs)
  • 1 detail page URL per item being answered about (proves the spec)
  • If detail page returns 404 → extract hrefs from index using Template 1, NOT guess
  • If guessing was used and failed, output MUST flag: ⚠️ URL 추측 — 검증 안 됨 and answer must say "공식 문서에서 확인하지 못했습니다"
Self-reflection checklist (before sending answer for spec-level questions)
  • Index URL was actually fetched (not just from memory)
  • Detail page was fetched for every exact claim in the answer
  • All URLs were extracted from real hrefs, not guessed from natural names
  • Source citation shows detail URL(s), not just index

If any unchecked → backtrack to drill-down step or downgrade answer to "확인하지 못함".

Insufficient evidence fallback

"공식 문서에서 확인하지 못했습니다. 내부 지식 기반으로 답변합니다." / "Could not verify from official docs. Answering from knowledge."

User feedback handling
  • "이 문서 아니야" / "wrong docs" → immediately try next fallback strategy
  • "코드만 보여줘" / "just show code" → switch to code-only output mode
  • "더 자세히" / "more detail" → fetch additional pages from the same docs

Disambiguation Patterns

When a query maps to multiple libraries:

By project context
  • "Router" in React project → react-router-dom
  • "Router" in Express project → express.Router
  • "ORM" in Python → check for sqlalchemy, django, tortoise-orm
  • "auth" → next-auth, passport, firebase-auth, supabase-auth etc.
Ecosystem conventions
  • "middleware" in Next.js → middleware.ts (edge middleware)
  • "middleware" in Express → app.use() pattern
  • "store" in Vue → Pinia (modern) or Vuex (legacy)
  • "state management" in React → useState/useReducer (built-in) or Zustand/Redux

Known Limitations

JS-rendered doc sites
  • developer.apple.com (SwiftUI, UIKit) → answer from knowledge, provide official URL
  • docs.oracle.com (Java SE) → answer from knowledge
Marketing llms.txt
  • neo4j.com/llms.txt → marketing index, not Cypher/docs. Use neo4j.com/docs/ directly.
Hugo sites
  • No detectable platform signals. Skip platform detection; go to sitemap.xml or GitHub source.
docs_map.md variant
  • Some sites publish the index under a different filename (e.g., *_docs_map.md) instead of llms.txt. Same concept: an AI-readable index of every documentation page — treat it exactly like llms.txt.

Error Handling

SituationAction
llms.txt returns 404Silently try next URL pattern, then fall back
llms.txt linked URL returns 404Strip .md extension and retry
Specific doc path 404Try parent path for table of contents
GitHub main branch 404Try master, then version-specific branches
Fetch returns empty/JS contentTry GitHub source or answer from knowledge
Fetch fails (network/timeout)Try an alternative URL, then report
Content is not documentation (marketing, landing page)Discard and try next strategy
Item in index but detail URL unknownRe-fetch index with Template 1 from references/webfetch-prompts.md — never guess
404 on guessed URL (spec-level)STOP guessing. Re-fetch parent index, extract actual hrefs. If still no result → "확인하지 못함"
No documentation foundInform user, answer from knowledge, suggest they provide the docs URL

Retrieval Optimization

  1. Index first — always fetch llms.txt (index) before llms-full.txt
  2. Targeted fetch — from index, identify the single most relevant page URL
  3. Section extraction — extract only the relevant section; do not dump entire page
  4. Progressive depth — if user asks "더 자세히", fetch additional pages
  5. Multi-page max — 3 pages for broad topics; summarize connections

Response Rules

  1. Language — match the user's language (Korean → Korean, English → English)
  2. Source citation — ALWAYS include documentation URL(s) at the end with "Source:" label
  3. Method transparency — note retrieval method (llms.txt / GitHub / sitemap / web search)
  4. Code examples — include them when the official docs provide them
  5. Version note — note the version (e.g., "React 19 기준", "as of Next.js 15")
  6. Conciseness — answer the specific question; don't dump entire pages
  7. Token awareness — for large docs, fetch the index first, then only the specific page needed

Output Format

Default mode
[Explanation based on official documentation]

[Code examples if relevant]

---
Source: [URL(s) fetched]
(version: X.Y | method: llms.txt/GitHub/sitemap/search)
Code-only mode (when user asks for code)
[Code examples with minimal inline comments]

---
Source: [URL(s)]

© fivetaku, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in plugins/docs-guide-codex/skills/docs-guide of fivetaku/gptaku-plugins-codex.

  • SKILL.md
  • references/fallback-strategies.md
  • references/knowledge-base.md
  • references/llms-txt-sites.md
  • references/regression-cases.md
  • references/webfetch-prompts.md

Open the folder on GitHubat commit d3b47fc

Compare with similar skills

Docs Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Docs Guide compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Docs Guide this skillfivetaku/gptaku-plugins-codex128—~3.5kAutomated safety check: PassMIT
Documentation LookupKaimingWan/oh-my-kiro107—~616Automated safety check: PassMIT
Ag2 Ag UIag2ai/build-with-ag2252—~1.7kAutomated safety check: PassApache-2.0
Htmxericrisco/rsc-harness156—~3.4kAutomated safety check: PassMIT
Senior Fullstackalirezarezvani/claude-skills28k1 repos~3.7kAutomated safety check: NotesMIT
Senior Fullstackborghei/Claude-Skills874—~1.7kAutomated safety check: PassMIT

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Categories

Questions about Docs Guide

What does Docs Guide do?

Fetch and explain official documentation for any library, framework, API, or service using an llms.txt-first strategy — triggers on "How do I…", "What is…", "How does X work", "Best practice for…"…. Docs Guide is an agent skill from fivetaku/gptaku-plugins-codex.

When should I use Docs Guide?

Docs Guide fits situations like: how does X work; best practice for… about React; langChain and any other library; on explicit doc requests (공식 문서.

How do I install Docs Guide in Claude Code?

Run `npx skills add fivetaku/gptaku-plugins-codex --skill docs-guide -a claude-code`. Or copy the skill folder (plugins/docs-guide-codex/skills/docs-guide in fivetaku/gptaku-plugins-codex) into .claude/skills/docs-guide in your project. Claude Code loads it when a task matches its description.

How do I install Docs Guide in Codex?

Run `npx skills add fivetaku/gptaku-plugins-codex --skill docs-guide -a codex`. Or copy the skill folder (plugins/docs-guide-codex/skills/docs-guide in fivetaku/gptaku-plugins-codex) into .agents/skills/docs-guide in your project. Codex loads it when a task matches its description.

Can I use Docs Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add fivetaku/gptaku-plugins-codex --skill docs-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/docs-guide, .gemini/skills/docs-guide, .github/skills/docs-guide and .opencode/skills/docs-guide in your project.

What does Docs Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: Docs Guide is instructions for the agent only. Our summary lists: Python 3.

Does Docs Guide access the network?

SKILL.md names 1 domain. In commands or code: raw.githubusercontent.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Docs Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Docs Guide use?

Docs Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Docs Guide use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.7k tokens, read only when the agent opens those files.

What are the alternatives to Docs Guide?

Skills that share tags, products or a category with Docs Guide: Documentation Lookup (KaimingWan/oh-my-kiro, 107 stars), Ag2 Ag UI (ag2ai/build-with-ag2, 252 stars), Htmx (ericrisco/rsc-harness, 156 stars) and Senior Fullstack (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Docs Guide?

fivetaku (a GitHub user) maintains it in fivetaku/gptaku-plugins-codex, which has 128 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on September 8, 2026.

Source: fivetaku/gptaku-plugins-codex on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.