智能缓存搜索

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

No annotations are present, so the description carries full burden. It discloses that the tool uses semantic similarity and operates on cache, which is basic. It does not mention side effects, authorization needs, or behavior when cache is empty, missing opportunities to add depth.

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, concise sentence that front-loads the key information. It is efficient and focused, though splitting into two sentences could improve readability slightly.

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?

An output schema exists, so return value details are unnecessary. However, the description lacks an explicit note that the tool only searches cached data, not the full database, which is critical context given sibling tools like search_papers. Overall adequate but could be more complete.

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?

Input schema coverage is 100% with all parameters described. The description adds no additional meaning beyond the schema, such as how to formulate queries or interpret thresholds. Baseline score of 3 is appropriate since schema already provides adequate documentation.

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 it searches for literature data in cache using semantic similarity, differentiating it from sibling tools like search_papers which may perform exact or database searches. The verb '查找' and resource '缓存中相关文献数据' are specific, and the mention of '语义相似度' distinguishes its fuzzy matching approach.

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 use for fuzzy searches in cache but does not explicitly specify when to use this tool over alternatives like advanced_search or search_papers. No guidance on prerequisites, exclusions, or when not to use it is provided.

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