rag_search

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

No annotations are present, so the description carries full responsibility for behavioral disclosure. It mentions the corpus is '公开' (public), implying a safe read operation, but gives no details on rate limits, authentication, pagination, or any side effects. Since this is a search operation that is presumably read-only, the lack of explicit behavioral context is a notable gap.

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, compact sentence that front-loads the primary action and then lists the filtering options. There is no redundant wording or unnecessary detail. It is efficient and easy to scan.

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 presence of an output schema, return values are covered, so the description need not explain them. However, for a search tool with 5 parameters and no annotations, the description leaves out usage context (when to use vs. siblings) and only vaguely explains the filter semantics. It does not specify the expected format of 'layer' or 'doc_type' values, and does not mention default behavior or limits. This is adequate for a basic tool but not comprehensive.

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 description coverage is 0%, so the description must compensate. It explains the meaning of three parameters (题号=case_id, 层级=layer, 文档类型=doc_type) as filters, which adds value beyond the generic schema titles. However, it does not explain the 'limit' parameter, and 'query' is self-evident but not explicitly described. The description partially compensates for the coverage gap.

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's function: '检索国赛优化与决策类公开语料' (retrieve public corpus for national competition optimization and decision-making). It names the specific verb '检索' (retrieve), the resource (public corpus), and immediately lists the filtering dimensions (case number, level, document type), which distinguishes it from sibling tools like rag_get_document or rag_list_sources that target specific items rather than search.

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?

No guidance is provided on when to use this tool versus its siblings. The description mentions filtering capabilities but does not state any conditions that would favor this over rag_get_case_context or rag_get_document, nor does it mention any exclusions or alternative tools. An agent would have to infer the appropriate use from the tool name alone.

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