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

The readOnlyHint annotation already indicates a safe read operation. The description adds valuable behavioral context by mentioning the provenance backing ('nearest archive colour's cultural provenance') and tunability by audience and tone, which 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?

Three sentences, each with a distinct purpose: what it generates, how it is backed, and how it can be used. No redundant information, and the primary action is front-loaded.

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 read-only content generation tool with an output schema, the description covers the core functionality, customization options, provenance, and use cases. It avoids over-explaining return values, which are handled by the output schema.

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% with descriptions for all parameters. The description enriches parameter understanding by naming example values for audience ('general public, designers, historians, children') and tone ('dinner party, academic, social media, brand copy'), reinforcing the tunable nature.

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 action ('Generate a hook sentence, three-sentence story, tweet, image prompt, and follow-up questions') and its resource ('any hex colour'). The specific list of output types distinguishes it from sibling tools like colour_story, which focus on a single narrative output.

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 explicitly provides usage contexts: 'to make archive colours shareable, to generate content, or to power a public-facing colour chat experience.' It does not mention alternatives or when-not-to-use, but the intended scenarios are clear.

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