audit_component

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

With no annotations, the description carries the full behavioral load. It discloses the output (score, grade, issues with fixes, approved items), implying read-only analysis. However, it does not mention any side effects, authorization, or error handling, though it does provide main behavioral expectations.

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?

Three concise, front-loaded sentences: purpose, output, and usage. Each sentence adds distinct value without unnecessary detail. The structure is clear and scannable.

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?

The description comprehensively explains what the tool returns (score, grade, issues, fixes, approved items) and gives a usage context. Given no output schema, this adequately explains the output. It lacks details on edge cases, but for a simple audit tool it is sufficient.

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% ('Código JSX ou TSX do componente para analisar'), which is adequate. The tool description adds context by explaining what the analysis does with the input, but it does not introduce new parameter-level meaning beyond what's in the schema.

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 it analyzes JSX/TSX code to detect AI-generated patterns, distinguishing it from siblings focused on themes and contrast. The verb 'Analisa' plus a specific resource makes the tool's purpose unambiguous.

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?

It explicitly instructs to use the tool 'antes de entregar qualquer componente React' (before delivering any React component), giving a clear when-to-use. It does not explicitly mention when not to use it, but the context is sufficient.

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