Get disclosure checklist

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

Annotations already indicate readOnlyHint=true. The description adds meaningful context: the tool retrieves a static rubric used for policy preparation, implying no side effects. It also explains the mapping to generate_policy fields, enhancing transparency beyond 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?

Two sentences with no repetition or filler. The first sentence conveys purpose and content, the second gives usage guidance. Efficiently front-loaded with essential information.

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?

Given no parameters and no output schema, the description is sufficient for an agent to select and invoke the tool correctly. It explains what the rubric contains, when to call it, and how it relates to generate_policy, covering all necessary context.

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?

The tool has no parameters, so the input schema is fully covered. The description does not need to add parameter details but adds value by explaining the tool's output and usage. Baseline 4 for 0 parameters 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 retrieves a rubric for scanning a codebase before generating or updating policies, and specifies the content: which SDKs, scripts, and patterns require disclosure and how they map to generate_policy fields. This distinguishes it from siblings like generate_policy or list_policies.

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 advises calling this before generate_policy when working inside the user's project, with a rationale that policies from actual code are better. While it doesn't enumerate all alternatives or exclusion cases, it provides clear context for primary use.

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