search_spec

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

With no annotations provided, the description fully discloses behavior: case-insensitive search, multi-language support, result structure, prerequisite (PROSUITE_SPEC_PATH), and error handling (returns error if no spec loaded). This exceeds expectations for transparency.

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 well-structured with a lead sentence, then details on query behavior, and a bullet list of result fields. It is informative without being excessively verbose, though the bullet list could be slightly trimmed.

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 absence of an output schema, the description completely explains the return values (name, category, allow_errors, condition_request, required_datasets) and covers prerequisites and error conditions. No gaps remain for an agent to use this tool effectively.

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?

Although schema description coverage is 0%, the description adds meaning to both parameters: 'query' is a natural-language string searched against condition fields, and 'max_results' is the maximum number of results. This goes beyond the schema which only provides types and default.

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 the loaded QA spec for conditions matching a natural-language query. It uses a specific verb-resource pair ('search the loaded QA spec') and distinguishes itself from siblings like list_conditions (which lists all) and describe_condition (which describes one condition).

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 implies when to use this tool (for natural-language search of conditions) and provides context such as multi-language support and a limit on results. It does not explicitly state when not to use it or compare to alternatives, but the context is clear enough for an agent to decide.

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