audit_tool_definition

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

With no annotations provided, the description carries the full burden. It explains that the tool returns top 3 findings covering specific areas (description quality, parameter schema precision, etc.) and accepts various formats. While it does not mention potential errors or limitations, for a read-only analysis tool the description provides sufficient behavioral context.

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 two sentences plus a brief list of coverage areas. It is front-loaded with the main action, contains no filler, and every sentence adds useful information. The structure is efficient and easy to parse.

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 the tool's moderate complexity (2 parameters, no output schema), the description is complete. It explains what the tool does, when to use it, what it returns (top 3 findings), and the aspects it covers. It also provides guidance on alternatives, making it self-contained for an agent.

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%, but the description adds value beyond the schema by specifying that the tool_definition parameter accepts JSON schema or natural-language format, and that context is optional for assessing overlap and discoverability. This extra information enhances parameter understanding.

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 analyzes a single tool/function definition and returns top 3 findings on tool-call reliability. It distinguishes itself from sibling tools by focusing on individual definitions, and mentions a paid tier for auditing entire tool sets, implying this tool is for single definitions only.

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 states when to use this tool: 'when a user shares a tool/function definition and asks why the model is calling it wrong, not calling it when expected, or confusing it with other tools.' It also provides an alternative: 'For auditing an entire tool set together, use the paid tier.'

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