map_to_taxonomy

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds rich context beyond them: deterministic lookup, no authentication, null-with-suggestions behavior, the rationale that a guess would change the score, and telemetry disclosure with an opt-out env var. This is well beyond what the structured fields provide.

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 with the core purpose, then trigger, then result semantics, then downstream usage. Five dense sentences, all earning their place, though the telemetry note could arguably be trimmed for a mapping 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?

Covers purpose, trigger, alternatives, return/error semantics, downstream routing, auth, and telemetry. With an output schema present, the description need not explain return values further, yet it already handles the null case that matters most for correct invocation.

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%, so the baseline is 3, but the description adds genuine meaning: instruct to pass only free-text fields and explains per-field return semantics (canonical value, what it matched on, or null with suggestions). It complements rather than repeats the schema.

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+resource: map everyday business language to canonical AI BVF values required by scoring tools. It clearly distinguishes itself from the sibling list_taxonomy, which serves a different need (enumerating every permitted value).

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?

Gives an explicit trigger ('CALL THIS when the user says customer service, procurement, banking... and the matching enum is not certain') and names the alternative list_taxonomy with the condition that selects it. It also tells the agent where the outputs flow next (score_initiative, diagnose_process, get_benchmark, portfolio tools).

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