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

Annotations declare readOnlyHint=true, so no destructive behavior needs disclosure. The description adds value by explaining the tool returns a canonical, exhaustive dataset and gives concrete examples, which helps set expectations. It doesn't discuss rate limits or auth, but for a read-only tool with a rich output schema, the disclosure is sufficient.

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 longer than average but well-structured: definition, content summary, usage guidance, and examples. Every sentence contributes, though the list of data categories could be slightly more compact. It is appropriately detailed for a complex tool with many optional parameters.

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 complexity, the description provides enough context to understand its role, what it returns, and when to use it. The output schema covers specific return values, and examples ground the behavior. Minor missing context like default archive count or batching behavior is already in the 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 description coverage is 100%, so the baseline is 3. The description doesn't add parameter-level detail, but it doesn't need to; the schema already explains hex, hexes, n_archive, include_physics, and include_cultural with defaults and examples.

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 opens with 'Canonical single-call colour truth object' and 'Returns everything known about a hex value', clearly stating the tool's purpose and scope. It explicitly distinguishes itself from siblings by naming colour_dna, archive_provenance, colour_cultural_risk, and colour_metrics, and positions itself as the foundational call ('Every other tool is built on this data').

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?

Provides clear guidance on when to use: 'Use this as the foundation call when you need the complete picture.' It also explains when not to chain separate tools by stating it 'Replaces chaining colour_dna + archive_provenance + colour_cultural_risk + colour_metrics separately', offering a direct alternative comparison.

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