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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the pipeline similarity to precheck_score but does not disclose whether the operation is read-only, has side effects, rate limits, or authentication requirements. It also does not describe any error conditions or edge cases. The description is thin on behavioral transparency for a tool with zero annotation coverage.

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 two sentences with no redundant words. It front-loads the purpose and immediately provides the key differentiator from precheck_score, followed by a direct instruction on how to pass input. Every sentence earns its place.

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?

Since there is no output schema, the description appropriately lists what will be returned (titles, sources, similarity scores, URLs), which is essential for the agent to know. It also mentions the pipeline and clarifies the focus. It does not elaborate on all parameters, but the schema covers those. The only minor gap is a lack of explicit usage conditions beyond the precheck_score contrast, but overall it is fairly complete for a retrieval-focused 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 100%, so the schema already documents all five parameters. The description adds the instruction 'Pass invention text via `code`', which reinforces the primary input but does not provide new semantic meaning beyond what the schema states (e.g., code is 'Source code or invention description'). This is baseline level for well-documented schemas.

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: returning the closest prior-art matches (titles, sources, similarity scores, URLs) for an invention. It also distinguishes itself from the sibling precheck_score by specifying it 'focuses on retrieval results', which helps an agent differentiate between the two.

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 a clear usage hint by comparing itself to precheck_score ('Runs the same analyze pipeline as precheck_score but focuses on retrieval results'), indicating when this tool is more appropriate than that sibling. However, it does not explicitly mention when not to use it or discuss other sibling alternatives, so it lacks explicit exclusions but offers solid contextual guidance.

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