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

With no annotations, the description carries the full burden and does a good job: it discloses the costs (300 credits), required authentication (api_key), and return values (policy_id and test scenarios). It also explains the formal solver mechanism. It stops short of describing failure modes or side effects like whether an existing policy is overwritten, but the provided details are substantive and non-obvious.

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, each carrying meaningful information: what it does, why it's different, and what you get/cost. It is front-loaded with the core purpose and avoids filler. No word is wasted.

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 creation tool with two params and no output schema, the description covers input, process, output, cost, and auth. It lacks guidance on how to use the returned policy_id with sibling tools like check_action, but this is not strictly required. The description is complete enough for an agent to invoke 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?

Schema coverage is 100% — both 'policy' and 'api_key' have descriptions that clearly explain their meaning and format. The tool description adds only a few redundant details (e.g., that api_key is required), so it does not significantly enhance what the schema already provides. Baseline 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 tool's function: converting plain-English policy text into a formal, solver-enforced guardrail. The verb 'Turn' plus the resource ('plain-English policy into... guardrail') is specific and distinguishes it from sibling tools like check_action or run_tests, which evaluate instead of create.

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 implies the primary use case (creating rules) and contrasts itself with LLM-judge-based approaches, providing clear context. However, it does not explicitly say 'use this instead of X' or mention any exclusions, such as when to use check_action instead.

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