search_library_docs

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return format ('JSON format with token statistics'), which is useful, but lacks critical details such as whether this is a read-only operation, potential rate limits, authentication requirements, error handling, or what 'token statistics' entails. The description is insufficient for a tool with mutation potential or external dependencies.

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

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

The description is concise with two sentences that efficiently cover the purpose and output format. It avoids unnecessary details but could be slightly more structured by front-loading key usage information. Every sentence adds value, though it's brief given the tool's complexity.

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

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

Given the complexity (searching across multiple sources), lack of annotations, and no output schema, the description is incomplete. It doesn't address how results are combined, sorted, or filtered, what 'token statistics' means, or error cases. For a tool with 2 parameters and external dependencies, more context is needed to ensure reliable use.

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

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It doesn't explain what 'library' expects (e.g., package name, repository URL) or how 'limit' affects results (e.g., number of docs, ranking criteria). The mention of 'PyPI metadata and GitHub repos' hints at the scope but doesn't clarify parameter usage or constraints.

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

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

The description clearly states the action ('Find docs') and resource ('for a library'), specifying it uses PyPI metadata and GitHub repos combined. It distinguishes from some siblings like 'fetch_pypi_docs' or 'fetch_github_readme' by mentioning the combined approach, but doesn't explicitly differentiate from all similar tools like 'search_crates' or 'search_docker_images'.

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

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

No explicit guidance on when to use this tool versus alternatives is provided. The description mentions the data sources (PyPI and GitHub) but doesn't specify when this combined approach is preferable over using individual tools like 'fetch_pypi_docs' or 'fetch_github_readme'. No exclusions or prerequisites are mentioned.

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