search_mechanics

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

Discloses that the search is offline, deterministic, and returns specific content. Mentions the licensing requirement. No destructive behavior is relevant, and with no annotations, this provides sufficient transparency for a search tool.

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 sentences, front-loading the core functionality. The licensing note adds necessary context. Could be slightly more concise but is efficient overall.

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 tool's simplicity, the description covers the return format, corpus source, attribution, and alternative tool. With an output schema present, no further detail on return values is needed. It is complete for effective tool selection.

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%, but the description does not explicitly explain the 'query' and 'limit' parameters beyond stating 'full-text search' and implying result selection. It does not mention default values or parameter details, leaving the schema to carry the burden.

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 it performs full-text search on a bundled wiki corpus, returning titles, snippets, and source links. It distinguishes itself from the sibling tool lookup_mechanic, which fetches from the live wiki.

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?

Explicitly states when to use this tool (offline corpus search) and when to use lookup_mechanic (for pages not bundled). Also mentions licensing attribution, providing clear usage context.

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