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check_secrets

Read-onlyIdempotent

Scan source code for hardcoded secrets such as API tokens, passwords, and private keys to prevent credential leaks before commit. Supports multiple programming languages.

Instructions

Scan source code (or snippet) for hardcoded secrets — cloud provider keys, API tokens, connection strings, private keys, passwords. Supports Python, JavaScript, TypeScript, Java, Go, Ruby, Shell, Bash. Use to detect leaked credentials before commit; for injection detection use check_injection. Free: 30/hr, Pro: 500/hr. Returns {total, by_severity, findings}. No data stored. The generic password-assignment rule is suppressed when a more-specific credential rule fires on the same line — one targeted finding per leaked secret, not two.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesSource code string to scan for secrets (can be a single file or code snippet)
languageNoProgramming language of the code. Must be one of: python, javascript, typescript, java, go, ruby, shell, bash, generic. Use 'generic' if unsure.generic

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond annotations (readOnly, idempotent, non-destructive), the description reveals that no data is stored and explains the suppression of generic password rules when specific credential rules fire, adding valuable 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is information-dense but well-structured, with a clear first sentence and logical flow. It is somewhat long but every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of secrets scanning and the presence of an output schema, the description covers return format, no data storage, and a notable behavioral suppression rule. It is complete and leaves no major gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the description does not add significant meaning beyond what the schema provides for the parameters. The extra context (supported languages, 'generic' default) is already in the schema descriptions or enum.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scans for hardcoded secrets in source code, lists supported languages, and explicitly distinguishes from the sibling tool check_injection. It uses specific verbs and resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides explicit guidance on when to use (before commit) and when not to use (for injection detection, use check_injection). It also mentions rate limits, helping the agent make appropriate choices.

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

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