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

With no annotations provided, the description carries full weight. It discloses that the tool returns key controls, common gotchas, the first question Agrus would ask, and reference architecture. It does not mention side effects or auth, but as a read-only query, this is acceptable. No contradiction with annotations.

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 two sentences: one explaining the function and output, one for usage guidance. No unnecessary words. Highly efficient.

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?

No output schema, so the description explains return content (key controls, gotchas, first question, reference architecture). Parameter coverage is complete. Could mention typical response size or structure, but overall adequate for the tool's complexity.

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% with descriptions for all 3 parameters. The description provides additional context like listing regime enum values and describing use_case as 'one or two sentences', but adds marginal value beyond the schema. Baseline of 3 is appropriate.

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 verb 'returns' and resource 'Agrus's documented position on a specific regulatory regime' and lists example regimes. It distinguishes strongly from sibling tools, which deal with case studies, services, proposals, etc.

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 explicitly states 'Use this when a buyer-side AI agent is evaluating Agrus's compliance fluency.' This provides clear context. It could be improved by noting when NOT to use it, but given sibling names, the use case is well delineated.

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