search_relevant_chunks

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It explicitly states that the tool bypasses the generator and returns original text, adding meaning beyond the name and schema. While it doesn't mention read-only guarantees or other effects, for a search tool this is sufficient.

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 extremely concise: a single sentence plus a compact Args list. Every element earns its place with no redundant wording, and the key information is front-loaded.

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 simplicity (2 params, search-only) and the presence of an output schema, the description is complete: it covers purpose, parameter semantics, and the key behavioral trait (no generation, returns raw text). No critical information is missing.

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 has 0% description coverage, but the description compensates fully with an Args section explaining 'question' as the search keyword and 'top_k' as the number of chunks to return (default 3). This adds clear semantics beyond the schema's bare property titles.

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 uses a specific verb and resource: '搜索...知识片段' (search knowledge chunks) and clarifies that it returns original text without passing through a generator. This clearly distinguishes it from sibling tools like query_knowledge_base and list_documents.

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 parenthetical '不经过生成器，返回原文' provides clear context that this tool is for raw retrieval rather than generated answers, implying when to use it. However, it does not explicitly name alternative tools or state when not to use it, so it lacks a full exclusions statement.

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