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

With readOnlyHint=true, the safety profile is already covered by annotations. The description goes beyond this by disclosing the computational approach (CIEDE2000 distance) and the full output set including verdict and recommendation. It does not mention rate limits or failure modes, but those are not essential for a read-only analytic tool.

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 compact and well-structured: it opens with the core question, follows with a terse input/output summary, and closes with the intended use case and value. Every sentence earns its place, with no repetition or 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 description gives enough high-level context for an agent to understand when and why to call the tool, and the schema plus output schema cover the remaining details. The only minor gap is that the 'Input:' list could imply all listed fields are required, when the schema only requires brand_hex, and the provenance parameter's subtle behavior is left entirely to the schema.

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 every parameter clearly, including complex semantics like competitor_provenance. The description only lists parameter names ('brand hex, brand name, competitor hexes and names, market, region') without adding format details or constraints, so it adds little beyond the 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 the tool's purpose: assessing whether a brand can own a colour against competitors in a market, and lists concrete outputs such as an ownership verdict and distinctiveness score. This distinguishes it from generic colour tools by emphasising ownership/collision, but it does not explicitly name or contrast sibling tools, so it falls short of full differentiation.

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 gives explicit situational guidance: 'Use before committing to a brand colour in a competitive market' and says it replaces manual colour distance checks and competitor palette analysis. It does not state when not to use it or name alternative tools, so it lacks the full when/when-not/alternatives coverage.

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