query_rag_knowledge

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint false), so the bar is lower. The description adds meaningful behavioral context beyond that: it discloses the lexical matching limitation and mentions that the response includes retrieval latency and a grounding verdict.

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?

Three tight sentences, front-loaded with the core action, then the important limitation, then the return shape. Every sentence earns its place with no filler.

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?

The presence of an output schema means return values need not be fully explained, and the description usefully notes latency and grounding verdict. But with 0% schema coverage, it should have described the tuning parameters (top_k, min_score_threshold) to make invocation unambiguous — that omission leaves a real gap.

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% and there are three parameters, yet the description only indirectly references 'query' and says nothing about 'top_k' or 'min_score_threshold'. An agent gets no guidance on what these parameters do or how to set them.

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?

States a specific verb (rank), resource (built-in knowledge corpus), and method (sparse TF-IDF vectors, cosine similarity). This clearly distinguishes it from the sibling tools, which handle events, compliance, approvals, and budgets.

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 intended usage (querying the corpus for lexical matches) and warns that paraphrased queries retrieve poorly, which is useful context for deciding when to use it. However, it never explicitly states when to choose this tool over alternatives or what prerequisites exist.

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