docs_link

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

With no annotations, the description must carry behavioral disclosure. It mentions the output format (one line each) and the nature of the links (official), but it does not describe edge cases like library not found or whether the tool performs verification. This is adequate for a simple lookup but not deeply detailed.

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 two short sentences, front-loading the purpose and adding a usage condition. Every word earns its place, with no unnecessary repetition or filler.

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?

The tool is simple (2 params, no output schema) and the description covers its main function and usage context. However, the phrase 'clamped answers' is ambiguous and could confuse an agent. Also, the effect of the optional topic parameter is not elaborated, but the schema covers it. Overall, reasonably complete for the tool's complexity.

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?

The schema descriptions cover both parameters (library and topic) fully, with library described as 'Library name as published on npm or PyPI' and topic as 'Optional topic to look up in the docs'. Since schema coverage is 100%, the description does not need to add extra parameter detail, so the baseline of 3 applies.

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 that the tool returns the official docs URL and GitHub repo for a library, with a one-line output for each. This specific verb+resource combination distinguishes it from sibling tools like should_i_use or alternatives, which serve different purposes.

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?

The phrase 'Use when the clamped answers are not enough' provides a specific context, indicating that this tool is a fallback when other answer sources are insufficient. It does not name sibling tools explicitly, but the conditional usage is clear enough for an agent to know when to invoke it.

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