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

With readOnlyHint=true, the annotation already declares safety. The description adds meaningful context by detailing the verdict options, output components (strengths, risks, alternatives), and the underlying methodology (CIEDE2000 + cultural intelligence). This goes beyond the minimal annotation, though it doesn't discuss response size or edge cases.

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 three sentences plus examples. It is front-loaded with the core action and returns, then adds methodology and concrete examples. Every sentence contributes, though the example list is slightly longer than strictly needed—still well under any verbosity threshold.

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 moderate complexity (5 parameters) and the presence of an output schema, the description covers the essential context: what it does, what it returns, and practical usage scenarios. It doesn't need to enumerate return fields, but it could have briefly mentioned how the verdict is derived for full completeness.

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 baseline is 3. The description adds extra value by illustrating parameter combinations through examples (e.g., 'heritage interior lime plaster wall' ties use_case and medium together). It clarifies how parameters interact without duplicating schema definitions.

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 evaluates a hex colour for a specific use case, market, and medium, and returns a decisive verdict. This specific verb+resource combination distinguishes it from sibling tools like colour_cultural_risk (which focuses only on cultural risk) and palette_verdict (which likely targets whole palettes).

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 via examples like 'luxury hotel brand in Japan' and 'ecommerce CTA button UK', showing applicability across use cases and markets. It doesn't explicitly name alternative tools or exclusion scenarios, but the context is clear enough for an agent to select this for single-colour use-case evaluations.

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