ai_search

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

The description states it returns a list of evidence, but with no annotations provided, it fails to disclose critical behavioral traits such as query language support, result ordering, pagination, or any side effects. The agent lacks information about what happens with the query or data_scope parameters beyond the schema.

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 single, short sentence that efficiently conveys the core function. It is front-loaded and concise. However, it could be slightly more structured by including usage hints, but it is not overly verbose.

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 has no output schema and only two parameters, the description is minimal. It explains the overall purpose but does not cover return format, error conditions, or how the tool integrates with siblings. The description is adequate for a simple search tool but leaves gaps.

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 coverage is 100% with descriptions for both 'query' and 'data_scope'. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate. The enum values for 'data_scope' are already clear in the schema.

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 performs AI search and returns a list of medical evidence related to a user question. It specifies the verb '检索' (search) and the resource '医学证据' (medical evidence), which is sufficiently clear. However, it does not explicitly differentiate itself from sibling tools like 'all_evidence_summary' or 'answer', which also deal with evidence or answers.

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 usage when a user has a question and wants evidence, but it provides no explicit guidance on when to use this tool versus alternatives like 'all_evidence_summary' or 'answer_stream'. There is no mention of prerequisites, exclusion criteria, or context boundaries.

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