atlas_api_helper

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It lists generated artifacts but does not state whether the tool writes files, requires authentication, or has side effects. This ambiguity leaves the agent unsure of the tool's runtime impact.

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 sentence with a clear serial list of features. It is relatively concise and front-loads the purpose, though it could benefit from better structure (e.g., bullets) to avoid a run-on feel.

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 tool is complex with 8 parameters and no output schema, but the description only provides a high-level feature list. It does not explain how endpoints, baseUrl, and library interact, nor what the final generated output looks like, leaving gaps for a tool of this complexity.

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%, so the parameter baseline is 3. The description repeats some parameter concepts (e.g., types, mocks, Zod schemas) but adds no new parameter-level meaning beyond what the schema already provides.

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 the tool as an 'API integration helper' and lists specific outputs: TypeScript types, React Query/SWR hooks, mock data, API clients with interceptors, and Zod schemas. This specific verb-resource pairing distinguishes it from the many sibling tools focused on analysis or refactoring.

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 tool is used for API integration code generation, but it provides no explicit when-to-use, when-not-to-use, or alternative tool references. It lacks contextual guidance for choosing this tool over siblings.

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