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

With readOnlyHint=true, the annotation provides the safety profile. The description adds process context: the archive finds the contradiction and Claude writes the outputs, including the specific output types (one-liner, short story, tweet) and an example. No destructive or side-effect behavior is relevant, so the description goes beyond the annotation.

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 an illustrative example. It front-loads the core purpose, then gives instructions and use cases. Every sentence earns its place with no redundancy, making it highly concise and well-structured.

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, the description covers purpose, usage, parameters, example output, and target use cases. The presence of an output schema handles return values, so the description is complete for an agent to select and invoke the tool correctly.

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 baseline is 3. The description reinforces parameter roles with examples (e.g., 'love' + 'red' returns dark green), but it doesn't add much beyond the schema's own descriptions. It clarifies the interaction between concept and expected_colour, earning a moderate score.

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 a specific verb+resource: 'Find the most surprising archive colour for a concept and generate a memorable one-liner subverting the obvious expectation.' It also provides concrete outputs (one-liner, short story, tweet) and an example, which distinguishes 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?

The description gives explicit use cases: 'Use this for public-facing demos, content, and brand storytelling.' It does not list alternatives or exclusion criteria, but the context is clear enough for an agent to choose this tool over others.

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