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secrets_detection

Scan code for leaked secrets, API keys, tokens, and credentials. Detects 16+ secret types including AWS keys, GitHub tokens, Stripe keys, private keys, JWTs, database URLs, and high-entropy strings. Returns redacted previews with severity levels and rotation recommendations. No external API — pure regex pattern matching. Costs $0.005 USDC per call.

Input Schema

NameRequiredDescriptionDefault
codeYesCode string to scan for secrets
filenameNoOptional filename for context (e.g. 'config.ts', '.env.example')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description does real work: it discloses the return shape (redacted previews, severity levels, rotation recommendations), the implementation model (pure regex, no external API), and the exact cost ($0.005 USDC per call). It stops short of discussing false-positive/negative characteristics of regex matching or any rate limits.

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?

Four short sentences, front-loaded with the action and detection coverage, then output, then implementation and cost. Every sentence carries distinct information and none repeats the schema.

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?

For a 2-parameter tool with no annotations and no output schema, the description is nearly complete: it explains what is returned, how detection works, and what it costs. Minor gap: it does not state input size limits or that filename only affects contextual labeling.

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 both parameters are documented in-schema, so the description baseline is 3. It adds no extra parameter meaning beyond what the schema says — for example, nothing about how large 'code' may be or how filename influences severity assignment.

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?

States a specific verb and resource — 'Scan code for leaked secrets, API keys, tokens, and credentials' — and enumerates the detected categories. No sibling in the list performs secret scanning (token_security and transaction_parse cover different ground), so an agent can route to it unambiguously.

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

Usage Guidelines3/5

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

Usage is implied by the resource (scanning source code or config strings), but there is no explicit when-to-use/when-not or comparison against any alternative tool. The note that filename is used 'for context' hints at typical inputs without stating prerequisites or exclusions.

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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