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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower. The description adds 'Static reference data. Free L0, no authentication required' and reveals that some traits are 'never returned about a third party,' which are meaningful behavioral details beyond the annotation flags.

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 compact and dense: a leading verb, precise content enumeration, a usage directive, and a qualification. Every sentence earns its place with no filler.

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 static reference tool with no output schema, the description covers what is returned (30 codes, categories, one-line semantics, discovery contexts, third-party exclusions) and when to use it. This is complete for the tool's simple nature.

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?

The tool has zero parameters and schema coverage is 100% (vacuously), so baseline is 4. The description doesn't need to elaborate on parameter meaning, and it doesn't introduce confusion by mentioning nonexistent inputs.

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 'List the canonical trait vocabulary' with specific content: 30 trait codes grouped by five named categories, one-line semantic per code, plus discovery contexts and third-party exclusions. This distinguishes it from sibling vocabulary tools like describe_competencies and list_archetypes.

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 before composing query_field trait_priorities or create_requirement trait_criteria,' giving a clear when-to-use. It does not mention when-not-to-use or alternatives, but the instruction is unambiguous and tied to specific workflows.

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