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secrets_entropy_scanner

Detect leaked secrets in source code by analyzing Shannon entropy and patterns for private keys, AWS access credentials, JWTs, and database connection strings.

Instructions

Shannon entropy and pattern analyzer scanning source code for leaked private keys, AWS access secrets, JWTs, and database connection strings. (0.030 USDC on Base L2)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payloadYesInput parameters or JSON string payload for the tool execution
paymentSignatureNoBase L2 USDC micropayment signature or transaction hash for x402 settlement

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It usefully discloses the analysis approach and the 0.030 USDC cost, but it does not state whether the tool is read-only, what it returns, or whether source code is transmitted externally. These are notable gaps, though the cost disclosure adds some transparency.

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 a single, front-loaded sentence that clearly communicates the tool's purpose and includes the relevant cost. There is no redundancy, and every clause contributes useful information.

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

Completeness2/5

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

With no output schema and no annotations, the description leaves important invocation details unstated: how to structure the payload, what the response contains, and how the payment signature relates to the 0.030 USDC fee. An agent can infer the general purpose but not fully understand the execution contract.

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%, so the baseline is 3. The description does not add meaningful parameter-level detail beyond the schema; the payload is described generically as 'Input parameters or JSON string payload' even though the tool's purpose implies it should contain source code.

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

Purpose4/5

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

The description clearly states the tool's function: analyzing Shannon entropy and patterns in source code to find leaked private keys, AWS access secrets, JWTs, and database connection strings. However, it does not differentiate itself from the closely related sibling detect_secrets_leak, so an agent may struggle to choose between them.

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

Usage Guidelines2/5

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

No explicit guidance is given about when to use this tool over detect_secrets_leak or other secret-related siblings. The phrase 'scanning source code' implies a context, but there are no conditions, exclusions, or alternative routing instructions.

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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