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

Annotations already declare readOnlyHint, idempotentHint and non-destructive. The description adds what the tool does NOT return (no score, verdict or language mapping), that it takes no parameters, is deterministic, requires no authentication, and has an opt-out telemetry behavior with the env var name. That is real behavioral context beyond annotations, though rate limits and output format are not detailed (output schema exists).

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?

Front-loaded purpose followed by call guidance, routing rule, and behavioral notes. Well organized, though the telemetry sentence is somewhat tangential to selecting the tool.

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 zero-param, annotated, read-only lookup with an output schema, the description covers purpose, routing, exclusions, and operational notes. Nothing an agent needs to select or invoke it correctly is missing.

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?

Zero parameters, so baseline is 4. The description reinforces this with 'Takes no parameters.' Nothing further is needed or possible.

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?

States a specific verb (Return) and resource (taxonomy values), and precisely scopes what is returned: 'the exact industry, function, AI-tier and readiness values every AI BVF calculation accepts.' The sibling map_to_taxonomy is named and distinguished.

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?

Explicit when-to-use: 'CALL THIS when the caller needs the complete allowed list or when a free-text value is not obvious.' Explicit routing to the alternative with examples of inputs that select map_to_taxonomy. No inference required.

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