get_fix_prompt

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

With no annotations provided, the description must carry the behavioral disclosure burden. It adds 'batched by severity,' which is a useful behavioral detail. However, it doesn't clarify the output format, any prerequisites, or potential side effects, though the 'Get' verb implies a read-only operation. This is acceptable but leaves some gaps.

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, front-loaded sentence of 13 words. It states the action ('Get'), the object ('AI-ready fix prompts'), and a key qualifier ('batched by severity') without any filler or repetition. 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?

This is a low-complexity tool with one parameter and no output schema. The description sufficiently conveys the purpose and a high-level view of the return value (prompts batched by severity). While it doesn't describe the exact response structure, for such a simple GET operation, the description is relatively complete.

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 single parameter auditId is fully described in the schema ('The audit UUID'), and the description adds no additional parameter semantics beyond confirming the relationship to an audit's findings. With schema coverage at 100%, the baseline of 3 is appropriate, though the description could have elaborated on expected values or constraints.

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 identifies a specific verb ('Get') and a specific resource ('AI-ready fix prompts for an audit's findings'), and adds a scoping detail ('batched by severity'). This distinguishes it from sibling tools like get_findings or get_fix_plan, which focus on raw findings or a fix plan rather than AI-ready prompts.

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 usage for fetching fix prompts for an audit's findings, but provides no explicit alternatives, exclusions, or guidance on when to use this tool versus siblings like get_fix_plan or get_findings. The context is clear but not elaborated beyond the basic purpose.

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