Is This Palette Working?

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

The description fully describes the output: verdict, score, colour roles, weakness, suggestion, and cultural grounding via archive matching. Annotations declare readOnlyHint=true, and the description aligns with a read operation. No contradictions.

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 plus examples, front-loaded with the main purpose. Every sentence adds meaningful detail without verbosity. Slightly dense but efficient.

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 covers input constraints (2-8 colors, required use_case), output structure (verdict, score, roles, weakness, suggestion), and usage context (examples). With an output schema present, the description is thorough and sufficient.

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 each parameter is described. The description adds value by specifying palette length (2-8 hex values) and including representative examples for `use_case`, `market`, and `medium`, improving semantics beyond 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 evaluates a palette of hex values for a use case, market, and medium, returning a verdict, score, role, weakness, and suggestion. Examples like 'premium cushion collection UK ecommerce' differentiate it from sibling tools like `palette_audit` or `colour_verdict`, though not explicitly contrasted.

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 concrete examples of when to use (e.g., 'SaaS brand identity global digital') but does not state when not to use or mention alternatives. Usage is implied through examples, but guidance is lacking.

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