Record Attestation

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

No annotations are provided, so the description must disclose behavioral traits itself. It states that 'Attestations are permanently recorded in the audit trail,' which warns the agent that the operation is non-reversible and persistent. It stops short of mentioning authorization or side effects beyond the audit trail, but covers the core write behavior.

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 three sentences: purpose, two-mode breakdown, and permanence. Every sentence adds distinct value with no redundant phrasing.

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?

With six parameters and no output schema, the description covers the essential usage context (human vs AI, statement expectations, audit permanence) and works alongside the schema's enums. It lacks explicit prerequisites (e.g., cleanroom must be initialized) or interaction notes with sibling logging tools, but is 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 67%, and the description adds context beyond the schema by explaining that for humans the statement confirms non-access and for AI it discloses training data/access scope. This maps directly to the 'statement' and 'training_data_note' parameters and clarifies the two attestation_type values. It doesn't describe the role enum, but the enum values are self-explanatory.

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 uses a specific verb ('Record') and resource ('attestation for the clean-room process'), and clearly separates human vs AI use cases. It does not explicitly mention sibling tools or alternatives, so it doesn't fully distinguish from overlap like cleanroom_ai_log, but the purpose is unambiguous.

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 provides clear context: use for human team members to confirm non-access, and for AI agents to record data access and training disclosures. It does not name when not to use it or compare to alternative tools, but the guidance is concrete enough to decide when to invoke.

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