retrieve_qa_knowledge

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

With no annotations, the description carries full burden. It discloses that unrecognized category values return a structured error, and k is clamped to [1,20]. It does not cover optional behavioral traits like read-only hint or rate limits, but the given details are specific and accurate.

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 concise and well-structured: first the purpose, then the return format, then parameter constraints. Every sentence provides valuable information without redundancy.

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 complexity (retrieval with filtering, error handling, clamping) and no output schema, the description covers the return format, error case, parameter constraints, and example categories. This is sufficient for an agent to correctly select and invoke the tool.

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 description coverage is 0%, so the description must compensate. It explains the category values and their valid set, error behavior for invalid input, k clamping, and the full return format with fields. This adds substantial meaning beyond the raw 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 it retrieves grounding chunks from a QA knowledge base, listing example sources and which domains are covered. It implicitly distinguishes from siblings like list_kb_sources (lists sources, not chunks) and review_qa_document (single document review).

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 explains what the tool does but provides no explicit guidance on when to use it vs. alternatives (e.g., list_kb_sources). The context of grounding suggests usage for retrieval in RAG, but no exclusions or alternatives are mentioned.

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