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Read-onlyIdempotent

Retrieve up-to-date, version-correct documentation for any library, framework, or API. Automatically detects the project's pinned version and fetches official docs, supporting direct URL input.

Instructions

Up-to-date official documentation for a library/framework/API (codehelper's local-first answer to Context7). Resolves the version this project pins from its manifests, then fetches version-correct docs preferring the llms.txt/llms-full.txt standard before HTML. library may also be a direct https URL (docs page, API reference, or OpenAPI page) to fetch it as-is. Unknown libraries resolve via npm/PyPI/crates metadata; if one is still missing, register it with docs_add. Network fetch is privacy-gated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoNoRepository name (optional; defaults to current MCP workspace)
topicNoOptional focus, e.g. 'app router', 'middleware', 'migrations'
formatNoResponse text encoding: toon (default, token-efficient) | json
libraryYesLibrary/framework name (next, react, laravel, cobra, django) OR a direct https docs/API URL
versionNoOverride version (default: detected from this project's manifest)
no_cacheNoBypass the on-disk docs cache
max_tokensNoApprox token budget for returned docs (default 5000)
approve_networkNoAllow network fetch for this call even if research is disabled in learning.json
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, open-world, idempotent, non-destructive. The description adds key behaviors: version resolution from manifests, preferred docs standard, direct URL support, caching, and privacy-gated network fetch.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise yet informative: a few sentences front-loaded with purpose, covering all key aspects without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Fairly complete given complexity: explains overall mechanism but does not explicitly describe the return format (beyond format parameter). Could mention that output is text content.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds context (e.g., library can be a URL, version override, privacy gate) but does not significantly extend beyond schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it fetches up-to-date official documentation for libraries/frameworks/APIs. It specifies version resolution, preferred format (llms.txt), and URL support, distinguishing it from siblings like web_search.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use it (to get docs) and mentions registering unknown libraries with docs_add, but does not explicitly state when not to use it or alternatives for similar tasks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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