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lib_docs

Fetch library documentation by name from npm, PyPI, crates.io, Go, and GitHub automatically. Accepts package names or GitHub repos, with optional saving.

Instructions

Fetch README/docs for a library by name. Tries npm → PyPI → crates.io → Go → GitHub automatically. Accepts react, numpy, serde, owner/repo, etc. Optionally saves to docs/libraries/.md.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesLibrary name. Examples: `react`, `express`, `numpy`, `serde`, `github.com/gin-gonic/gin`, `owner/repo`.
saveNo
refreshNo
versionNo
ecosystemNo
Behavior4/5

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

The description discloses key behavioral traits: the automatic fallback sequence across package registries and the optional side effect of saving to a file. Since no annotations are provided, this adds meaningful context beyond the schema, though it omits failure handling and return behavior.

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?

The description is exceptionally concise at two sentences, with the main purpose stated first and supplementary details following. Every word contributes useful information; no redundant or vague language.

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

Completeness2/5

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

The description leaves significant gaps: there is no output schema, yet the return value (does it return content or just save to file?) is not explained. The `refresh`, `version`, and `ecosystem` parameters are completely undocumented, and the empty enum for ecosystem is confusing. The description covers only the basic use case.

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?

The description adds value for the `name` parameter (format examples) and the `save` parameter (destination path), but schema coverage is low (20%) and the remaining parameters (refresh, version, ecosystem) are not explained in either schema or description. The description does not fully compensate for the coverage gap.

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 the verb 'Fetch' and the resource 'README/docs for a library by name', with concrete examples like `react` and `owner/repo`. It differentiates itself from sibling tools (web_search, fetch_url, search_docs, list_docs) by focusing specifically on library documentation retrieval.

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 provides clear context: use this tool when you need docs for a specific library, with automatic ecosystem detection. It does not explicitly state exclusions or alternative tools, but the intended usage is evident from the phrasing and examples.

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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