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decagondev

MCP Factory

by decagondev

scan_secrets

Scans a codebase directory for exposed secrets, API keys, and credentials, including AWS keys, GitHub tokens, and database connection strings.

Instructions

Scan a codebase directory for exposed secrets, API keys, and credentials.

Detects AWS keys, GitHub tokens, GCP keys, Slack tokens, JWTs, private keys, database connection strings, and generic hardcoded secrets.

Use this when asked to check for leaked credentials or secrets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must fully convey behavior. It lists detectable secret types (AWS keys, GitHub tokens, etc.) but does not describe scanning behavior (e.g., recursion, file size limits, handling of non-code files). This is adequate for a simple tool but lacks behavioral depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description is two short paragraphs. The first sentence immediately states the core purpose. Examples and usage are presented efficiently. No unnecessary words or repetition.

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

Completeness4/5

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

Given the tool has only one parameter and an output schema (assumed to document return values), the description covers purpose and usage adequately. It does not mention edge cases (e.g., path not found) but is complete for typical use.

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?

The only parameter is 'path', which the description clarifies as 'a codebase directory'. With 0% schema description coverage, the description adds essential meaning. However, it does not explain expected format (absolute/relative) or constraints (must be directory), which would improve semantic clarity.

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 action ('Scan a codebase directory') and the resource ('exposed secrets, API keys, and credentials'). It lists specific examples, making the purpose unmistakable. Among siblings like scan_codebase, scan_code_quality, and scan_security_patterns, the focus on credentials distinguishes it well.

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

Usage Guidelines4/5

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

The description explicitly says 'Use this when asked to check for leaked credentials or secrets.' This provides a clear when-to-use clause. However, it does not mention when not to use it or provide alternatives among siblings, which would strengthen guidance.

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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