search_docs

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

No annotations are provided, so the description carries the full burden. It explains the behavioral differences between keyword and semantic search per filter, and discloses the default behavior. It does not cover side effects or auth needs, which are minimal for a read-only 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 a multi-line docstring with an Args section, which is reasonably concise but could be more streamlined for JSON. It is front-loaded with the main purpose, but the format uses Python-style notation that may be less familiar in some contexts.

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?

With 5 optional parameters, an output schema, and a comprehensive description covering all parameters and behavioral nuances, the tool definition is complete. No critical gaps are present.

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. The docstring provides detailed explanations for each parameter, including filter options, project usage, limit, and min_depth, adding significant meaning beyond the schema titles and defaults.

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 tool searches markdown corpus and IP documents with various filters, specifying the verb 'search' and the resource. It distinguishes from sibling tools like search_conversations and search_summaries.

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 description provides context for each filter option (e.g., default keyword search, 'ip' for semantic search), but does not explicitly state when not to use or mention alternative tools. It offers good guidance on when to use different filters.

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