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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: it explains the parsing source, the family/shade hierarchy (red also finds dark red, maroon, burgundy), match semantics, and the claimed=false behavior. This gives an agent a solid mental model of how results are computed without contradicting the annotations.

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 dense but well-structured: it front-loads the core purpose, then systematically covers levels, match modes, claimed behavior, and available modes. Every sentence contributes useful information, and there is no filler or repetition. It is longer than average, but the tool's complexity justifies the length.

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 (11 parameters, 6 modes, no output schema), the description covers the main decision points: level, match, claimed, and all modes. It does not detail return values or examples, but the schema already documents parameters. The description is complete enough for an agent to know what to call and how to configure it, though an example invocation would have pushed it to 5.

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 coverage is 100%, so the baseline is 3, but the description adds value beyond the schema. It clarifies the level values with concrete examples, explains match semantics in plain language, and defines the claimed=false behavior. The description also expands on mode outcomes, making the parameter meanings more actionable than the schema alone.

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 opens with a specific verb and resource: 'Searches or counts U.S. trademarks by the colors they claim, parsed from USPTO color-claim statements.' This clearly distinguishes the tool from siblings like search_trademarks or search_mark_statements by focusing on color-claim parsing. It also names the exact data source (USPTO color-claim statements), leaving no ambiguity about what the tool operates on.

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 when to use the tool (whenever color claims are the search dimension) but does not explicitly state alternatives or when not to use it. It provides rich in-tool configuration guidance (levels, match modes, claimed=false), but no comparison to sibling tools or exclusions. The usage context is clear from the tool's niche, but explicit routing guidance is absent.

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