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Agent skill

Docs Seeker

by avibebuilder in avibebuilder/claude-prime

Fetch up-to-date documentation for any library, framework, API, or service into context.

MITAuto-check passedDatabases

Install Docs Seeker

skills CLI
$ npx skills add avibebuilder/claude-prime --skill docs-seeker -a claude-code

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

GitHub CLI
$ gh skill install avibebuilder/claude-prime docs-seeker --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/avibebuilder/claude-prime.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/docs-seeker .claude/skills/docs-seeker && 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-seeker
GitHub stars
120
Used in
1 other repo
Token cost
~1.4k tokens
SKILL.md length
714 words
Files
1
Skills in repo
19
Repo updated
First seen
Licence
MIT

At a glance

Fetch up-to-date documentation for any library, framework, API, or service into context.

  • Works in 4 steps: llms.txt on the official docs site —… → Context7 — a mirror that ingests GitHub… → GitMCP — any GitHub repo is accessible… → …
  • The user wants to look up API references
  • SKILL.md covers Why fetch instead of recall, The source hierarchy (and why), Topic scoping and Reading the docs you find, plus 3 more sections
  • Reaches context7.com

What it does

Docs Seeker is an agent skill from avibebuilder/claude-prime. Fetch up-to-date documentation for any library, framework, API, or service into context. Use when the user wants to look up API references, check function signatures or required fields, find feature-specific docs, or verify how an external tool actually works. Triggers for queries about third-party libraries like Stripe, SQLAlchemy, Tailwind, FastAPI, shadcn, Drizzle, Hono, Better Auth — any time the answer lives in official docs rather than in the project codebase. Use this instead of guessing from trained…

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases, covering ORMs and data access, Design systems and CSS and styling. It works with shadcn/ui, FastAPI, Hono and Better Auth. The repository describes itself as: You've heard Claude Code can do amazing things. Skills, hooks, agents, memory systems — but who has time to figure all that out? Claude Prime sets it up for you in one command. The licence is MIT.

When your agent uses it

  • The user wants to look up API references
  • Check function signatures
  • Required fields
  • Find feature-specific docs

Example prompts

  • “/docs-seeker”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. llms.txt on the official docs site — hand-curated by the project, AI-optimized, token-dense, always current. This is the ideal source when…
  2. Context7 — a mirror that ingests GitHub repos and exposes them at https://context7.com/{org}/{repo}/llms.txt, with optional…
  3. GitMCP — any GitHub repo is accessible by swapping github.com → gitmcp.io in the URL. Useful when Context7 doesn't have the repo indexed…
  4. WebSearch — last resort. Slower, noisier, and you'll spend tokens filtering results. Only fall here when the three structured sources all…

What it can do on your machine

Read from SKILL.md and the folder at commit 80bcfa4. 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:

    • context7.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 Seeker loads about 1.4k tokens when it runs. Until then it costs about 138 tokens; SKILL.md has 714 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~138
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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 avibebuilder/claude-prime at commit 80bcfa4, republished under its MIT licence (© avibebuilder). 714 words, ~1,357 tokens.

Download SKILL.mdSave it as .claude/skills/docs-seeker/SKILL.md (or your agent's skills folder).
name
docs-seeker
description
Fetch up-to-date documentation for any library, framework, API, or service into context. Use when the user wants to look up API references, check function signatures or required fields, find feature-specific docs, or verify how an external tool actually works. Triggers for queries about third-party libraries like Stripe, SQLAlchemy, Tailwind, FastAPI, shadcn, Drizzle, Hono, Better Auth — any time the answer lives in official docs rather than in the project codebase. Use this instead of guessing from trained knowledge, which is stale.

Why fetch instead of recall

Trained knowledge rots. Library APIs rename fields, deprecate hooks, restructure auth flows, and change defaults between minor versions. Answering from memory is how you get confidently wrong code. Replace memory with retrieval — cheaply, from sources designed for AI consumption.

The source hierarchy (and why)

Prefer sources in this order. The ranking is about signal per token, not just availability.

  1. llms.txt on the official docs site — hand-curated by the project, AI-optimized, token-dense, always current. This is the ideal source when it exists. Try {official-docs-url}/llms.txt first for any library with a docs site; many projects ship one even if they don't advertise it. If llms.txt is just an index of links, follow the most relevant ones. llms-full.txt exists on some sites and contains the full corpus — only reach for it when the user explicitly wants comprehensive docs, since it's large.

  2. Context7 — a mirror that ingests GitHub repos and exposes them at https://context7.com/{org}/{repo}/llms.txt, with optional ?topic={keyword} filtering. Use this when the project has no official llms.txt, or when you want to scope to one feature. The {org}/{repo} path mirrors GitHub exactly — derive it from the user's package.json, imports, lockfile, or the project's GitHub URL rather than guessing. For docs sites without a clear repo, Context7 also hosts https://context7.com/websites/{normalized-path}/llms.txt.

  3. GitMCP — any GitHub repo is accessible by swapping github.com → gitmcp.io in the URL. Useful when Context7 doesn't have the repo indexed, or when you need source-of-truth README/examples straight from the repo.

  4. WebSearch — last resort. Slower, noisier, and you'll spend tokens filtering results. Only fall here when the three structured sources all miss. When you do search, query for "{library} llms.txt" first — it often surfaces an official or community-maintained one.

On any 404, timeout, or empty response: move to the next tier immediately. Never retry a failed source.

Topic scoping

When the user's query targets a specific feature (e.g., "shadcn date picker", "Next.js middleware", "Stripe webhooks"), append ?topic={keyword} to the Context7 URL to narrow the fetch. Pick a short root keyword that captures the feature — judgment call, no rigid rules. The goal is fewer tokens, higher relevance. If the topic URL returns nothing useful, drop the topic and try the general URL.

Show full SKILL.md (349 more words)Show less

Reading the docs you find

Once you have URLs, the question is how to read them without polluting the main context.

  • A handful of small pages, or content the orchestrator clearly needs verbatim: read directly with WebFetch. Fast, simple, no overhead.
  • Many pages, or large pages where you only need specific answers: fan out to parallel subagents, each reading a subset and returning a condensed summary. This protects the main context window from doc bloat and parallelizes I/O. Use judgment on fan-out count — a couple for moderate sets, more for large ones. The tradeoff is latency/tokens vs. main-context pollution; lean toward subagents whenever the raw docs would be noisy relative to what the orchestrator actually needs.

When delegating to subagents, tell them exactly what question to answer and what to return (e.g., "return the exact signature and required fields for stripe.webhooks.constructEvent, plus any version notes") — not "summarize these docs". Specific asks give specific answers.

Version awareness

Before fetching, check what version the project actually uses — package.json, requirements.txt, go.mod, lockfiles. Fetching the latest docs when the project is pinned two majors behind is a common way to hand back wrong answers. If a version-specific doc path exists (e.g., /v2/llms.txt, /docs/4.x/), prefer it.

Gotchas

  • Don't fabricate. If every source misses, say so clearly and ask the user for a URL or a different approach. A made-up API signature is worse than "I couldn't find it."
  • Don't over-fetch. The orchestrator asked a question; pull what answers it, not the entire manual. Every token you add competes for attention downstream.
  • Don't trust your own cache. If you recall that a library's docs live at a certain URL, verify — sites reorganize. A fresh fetch beats a confident memory.
  • Report what you used. When you hand results back, note which source succeeded (llms.txt / Context7 / GitMCP / WebSearch) and the URLs fetched. This lets the orchestrator judge freshness and lets the user follow up.

Constraints

  • Use WebFetch to read URLs. Do not invoke MCP servers for this.
  • Prefer llms.txt over llms-full.txt unless comprehensive docs are explicitly requested.
  • Never retry a failed source — move down the tier list.

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

Files

Just SKILL.md in .claude/skills/docs-seeker of avibebuilder/claude-prime.

Open the folder on GitHubat commit 80bcfa4

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in avibebuilder/claude-prime, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Docs Seeker 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 Seeker compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Docs Seeker this skillavibebuilder/claude-prime1201 repos~1.4kAutomated safety check: PassMIT
Supabase Pythonalinaqi/maggy707—~4kAutomated safety check: NotesMIT
Fastcrudbenavlabs/fastcrud1.6k—~5kAutomated safety check: PassMIT
Mastering Python SkillSpillwaveSolutions/agent-brain120—~1.4kAutomated safety check: NotesMIT
Python Backendyonatangross/orchestkit288—~2.8kAutomated safety check: NotesMIT
Python Best Practicesc0x12c/ai-toolkit106—~676Automated safety check: PassNone

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Works with

Categories

Questions about Docs Seeker

What does Docs Seeker do?

Fetch up-to-date documentation for any library, framework, API, or service into context. Docs Seeker is an agent skill from avibebuilder/claude-prime. Fetch up-to-date documentation for any library, framework, API, or service into context.

When should I use Docs Seeker?

Docs Seeker fits situations like: the user wants to look up API references; check function signatures; required fields; find feature-specific docs.

How do I install Docs Seeker in Claude Code?

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

How do I install Docs Seeker in Codex?

Run `npx skills add avibebuilder/claude-prime --skill docs-seeker -a codex`. Or copy the skill folder (.claude/skills/docs-seeker in avibebuilder/claude-prime) into .agents/skills/docs-seeker in your project. Codex loads it when a task matches its description.

Can I use Docs Seeker 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 avibebuilder/claude-prime --skill docs-seeker -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-seeker, .gemini/skills/docs-seeker, .github/skills/docs-seeker and .opencode/skills/docs-seeker in your project.

What does Docs Seeker need to run?

SKILL.md names no scripts, command-line tools or credentials: Docs Seeker is instructions for the agent only.

Does Docs Seeker access the network?

SKILL.md names 1 domain. In commands or code: context7.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Docs Seeker 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 Seeker use?

Docs Seeker 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 Seeker use?

About 1.4k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Docs Seeker?

Skills that share tags, products or a category with Docs Seeker: Supabase Python (alinaqi/maggy, 707 stars), Fastcrud (benavlabs/fastcrud, 1.6k stars), Mastering Python Skill (SpillwaveSolutions/agent-brain, 120 stars) and Python Backend (yonatangross/orchestkit, 288 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Docs Seeker?

avibebuilder (a GitHub organization) maintains it in avibebuilder/claude-prime, which has 120 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on May 16, 2026.

Source: avibebuilder/claude-prime on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.