ai_governance_assess

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

With no annotations, the description carries the full burden of behavioral disclosure. It lists output artifacts but does not state whether the tool is read-only, whether it modifies anything, what authentication or rate limits apply, or how the assessment process behaves. This is a significant transparency gap for a tool that likely makes external calls or computations.

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 a single, focused sentence that front-loads the core purpose and lists key outputs without redundancy. Every clause adds value, making it efficient and easy to scan.

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?

The description gives a good overview of outputs but lacks guidance on input requirements, return format, or any operational context. Since there is no output schema, the description partially compensates by listing expected outputs, but it does not address how to construct inputs or interpret results.

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 description coverage is 100%, so parameters like sector, jurisdiction, deployment_type, and ai_system_description are already defined. The description adds no additional parameter-level context, which is acceptable given the high schema coverage, though the 'additional_context' parameter remains vague.

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 performs an AI governance assessment and enumerates specific outputs such as risk classification, compliance gaps, and certification pathway. It distinguishes itself by explicitly combining CSOAI and CASA frameworks, though it does not directly compare against sibling tools.

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 no explicit guidance on when to use this tool versus alternatives like ai_sector_compliance or ai_certification_bundle. The purpose is implied, but no conditions, exclusions, or alternative recommendations are given.

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