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

The readOnlyHint annotation is consistent, and the description adds valuable behavioral detail: the result already carries rendered palette downloads, users should show them, archive anchors must not be presented as recommended colours, and final recommendations should route through palette_finalize. This goes well beyond what annotations convey.

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 every sentence earns its place: core behavior, output details, examples, download behavior, an important warning, and a routing instruction. It is front-loaded with what the tool does and structured so an agent can act on it without re-reading.

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?

For a tool with an output schema and a read-only annotation, this description is remarkably complete. It covers input constraints, illustrative use cases, result contents, presentation guidance, a safety warning, and the correct follow-up tool call, leaving no critical ambiguity for an agent.

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 palette, use_case, market, and medium. The description reinforces these semantics with context and examples, but does not add meaning beyond the schema, so the baseline of 3 is appropriate.

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 ('evaluate') and resource ('a palette of 2-8 hex values'), and enumerates concrete outputs: a verdict, a score, colour roles, biggest weakness, and a suggestion. This clearly differentiates it from adjacent tools like palette_analyse or palette_compare, since none promise this specific verdict format.

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 conveys when the tool applies ('Evaluate a palette... for a use case, market, and medium') and gives realistic examples. It also gives explicit downstream routing: call palette_finalize once if you choose a final palette of your own. It does not name alternative comparison/analysis tools or exclusion conditions, so it stops short of a 5.

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