Get an AI Governance Unit

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds value beyond this by specifying what the returned governance unit includes: scope, key requirements, implementable controls, a checklist, and common pitfalls. This gives the agent a concrete idea of the response's substance without contradicting any annotation.

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?

Two sentences with no filler: the first front-loads what the tool returns, and the second gives actionable workflow guidance. Every word earns its place.

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?

For a simple read-only retrieval tool, the description is complete: it names the lookup key, states the workflow, summarizes the payload, and the output schema covers return details. The annotations cover safety and idempotency, so nothing critical is missing.

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 both `slug` and `locale` are already fully documented. The description only echoes the slug-based lookup and adds no additional parameter-level meaning, so the schema carries the burden and the baseline of 3 applies.

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 a specific verb ('Get'), a specific resource ('one AI governance unit'), and the lookup mechanism ('by slug'). It also lists the returned content areas, which makes the tool's purpose concrete and distinguishes it from list-oriented siblings like list_governance.

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 provides a usage workflow: use this tool once `search` or `list_governance` has returned a slug. This directly prevents misuse by telling the agent when the tool is appropriate relative to its siblings.

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