find_best_match

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

With no annotations provided, the description carries the full burden. It discloses the algorithm type ('字符匹配算法' - character matching algorithm) and the tool's suitability for quick verification/location. However, it doesn't mention potential limitations (e.g., accuracy, speed, rate limits), authentication needs, or error handling. It adds some behavioral context but leaves gaps for a tool with no annotations.

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 and concise. It starts with the core purpose, adds usage guidelines, and includes clear sections for Args and Returns. Every sentence adds value, though the 'ctx' parameter note could be more integrated. It's appropriately sized for a single-parameter tool.

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 moderate complexity (1 parameter, 100% schema coverage, output schema exists), the description is fairly complete. It covers purpose, usage, parameters, and return values. The output schema handles return details, so the description doesn't need to explain them. However, with no annotations, it could benefit from more behavioral context like limitations or prerequisites.

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 100%, so the baseline is 3. The description adds value by explaining the parameter 'query' as '论文标题或关键词' (paper title or keywords), which clarifies its semantic purpose beyond the schema's basic description. However, it doesn't provide additional details like format examples or constraints beyond what the schema already covers (minLength: 1).

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 purpose: '快速查找与输入标题最匹配的 CNKI 论文' (quickly find the best matching CNKI paper for an input title). It specifies the verb (find), resource (CNKI papers), and scope (best match). However, it doesn't explicitly differentiate from sibling tools like 'search_cnki' beyond mentioning it uses a 'character matching algorithm'.

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 some usage context: '适合用于验证论文标题或快速定位特定论文' (suitable for verifying paper titles or quickly locating specific papers). This implies when to use it, but it doesn't explicitly state when NOT to use it or mention alternatives like 'search_cnki' or 'get_paper_detail'. The guidance is helpful but incomplete.

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