scan_public_api

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

Annotations indicate readOnlyHint=true, idempotentHint=true, etc., establishing it as a safe, non-destructive operation. The description adds behavioral detail: it extracts and probes endpoints to map auth requirements, implying network requests. This goes beyond what annotations alone convey, making the behavior transparent.

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 three sentences, front-loading the core purpose in the first sentence. Each sentence adds necessary detail without redundancy. It is efficient and succinct, earning its length.

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?

For a tool with one parameter and no output schema, the description provides a thorough overview of the process and outcome. It covers what the tool does, how it works, and a key constraint (no source code). Minor gap: the output format is not described, but the tool's purpose is clear enough for an AI agent to understand its use.

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 'url' has a schema description: 'The URL to audit (e.g., https://example.com).' The tool description enhances this by explaining how the URL is used (crawling HTML, extracting JS). This adds semantic value beyond the schema, clarifying the input's role.

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 explicitly states the tool's function: 'API surface discovery from frontend JavaScript.' It details the process of crawling HTML for script tags, extracting API URLs from JS bundles, and probing endpoints. This clearly distinguishes it from sibling tools, none of which focus on frontend JS scanning.

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 context by noting 'No source code needed,' indicating it works purely from the frontend. However, it does not explicitly state when to avoid this tool or compare it to alternative audit tools (e.g., audit_security). The context is clear but lacks explicit exclusions.

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