scan_repo_secrets

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It discloses the need for a GITHUB_TOKEN for best results and the security research scope. However, it does not explain behavior without the token (e.g., rate limits, reduced results) or any other traits like idempotency or side effects. This is adequate but not comprehensive.

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 concise (3 sentences) and front-loaded with the main purpose. It includes necessary details like token requirement and use case. Minor improvement could be separating use case or adding a note about output, but overall efficient.

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 has a single parameter and an output schema (not described), the description is reasonably complete. It explains what the search term should be, the purpose, and prerequisites. The existence of an output schema means return values don't need elaboration. However, it could mention the response type (e.g., list of matches) for completeness.

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 input schema has zero description coverage (0%), so the description must compensate. It provides detailed guidance: 'CVE ID, tool name, or keyword to search for in public repo files (e.g. CVE-2024-1234, AWS_SECRET_ACCESS_KEY, log4j).' This adds significant meaning beyond the schema's type and title.

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 searches GitHub public repositories for exposed credentials/secrets related to a search term. It specifies the search term can be a CVE ID, tool name, or keyword, providing examples (e.g., CVE-2024-1234, AWS_SECRET_ACCESS_KEY, log4j). This distinguishes it from sibling tools like lookup_cve or check_exploit_availability, which focus on CVE details and exploit availability, respectively.

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 mentions 'Requires GITHUB_TOKEN for best results. For security research only.' This provides context on prerequisites and intended use. While it doesn't explicitly state when not to use it or compare with alternatives, the specificity of the tool (searching for secrets in repos) makes it clear when to invoke.

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