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

The description discloses the behavioural process: 'The archive finds the contradiction and Claude writes the one-liner, short story, and tweet,' and shows an example. This adds value beyond the readOnlyHint annotation, which only indicates no side effects. No contradiction with 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 front-loaded with the main purpose, followed by input instructions, an illustrative example, and a use-case sentence. It is compact and every sentence contributes meaningful information without redundancy.

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 the tool's purpose, input details, example output, and target use cases. Since an output schema exists, the return format is already documented. It does not mention n_results explicitly, but the schema covers that, so no significant gaps.

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 descriptions already cover all three parameters (100% coverage), so baseline is 3. The description adds semantics by providing concrete examples (e.g., 'love', 'red') and illustrating how they interact (love + red returns Shakespeare's dark green), which helps the agent choose appropriate values.

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 function: find the most surprising archive colour for a concept and generate a one-liner, short story, and tweet subverting expectations. This specific verb+resource combination and the mention of creative outputs distinguish it from sibling tools like archive_search or colour_story.

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?

It explicitly says 'Use this for public-facing demos, content, and brand storytelling,' providing a clear when-to-use context. It does not explicitly state when not to use it or name alternatives, but the use case is sufficient.

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