map_to_regulation

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

With no annotations provided, the description fully details behavior: read-only, stateless, idempotent, safe to repeat, rate limits (10/day free), authentication needs, error handling (structured errors), and data privacy (no storage/logging). This far exceeds typical transparency.

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 well-structured with headings but is verbose, especially the behavioral transparency section which repeats information from the earlier behavior list. While comprehensive, it could be more concise.

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 presence of an output schema, the description covers all necessary aspects: purpose, parameters, behavior, rate limits, error handling, idempotency, and data privacy. Nothing critical is missing for an AI agent to use this tool correctly.

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?

Despite 0% schema description coverage, the description explains each parameter in an 'Args' section: ai_bom_json, regulation (with default eu_ai_act), and api_key. While explanations are somewhat generic, they add meaningful context beyond the schema's bare definitions.

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 purpose: mapping an AI-BOM against a specific regulatory framework's technical documentation requirements. It lists supported frameworks (eu_ai_act, nist_ai_rmf, us_eo_14028, iso_42001) and is distinct from siblings like audit_ai_bom_completeness or generate_ai_bom.

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 includes explicit 'When to use' and 'When NOT to use' sections, guiding the AI agent on appropriate contexts. It advises against real-time production use without human review, which sets clear expectations.

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