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glincker

glin-profanity-mcp

by glincker

scan_secrets

Detect leaked credentials, API keys, and tokens in text. Returns detailed scan results with pattern IDs and positions to block or flag exposed secrets.

Instructions

Scan text for leaked credentials, API keys, tokens, and other secrets. Returns a full ScanResult with per-match details including pattern id, family, and character positions.

Input Schema

NameRequiredDescriptionDefault
textYesThe text to scan for secrets
blockOnAnyNoWhen true (default), any detected secret causes a BLOCK decision
minEntropyNoMinimum Shannon entropy required for high-entropy pattern matches (default: 4.0)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A3.6/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It does add useful context about the return shape ('full ScanResult with per-match details including pattern id, family, and character positions'), but says nothing about the BLOCK decision driven by blockOnAny, the 50,000-character input cap, or cost/latency behavior.

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?

Two sentences, zero filler, with the action front-loaded and the return format trailing. Every clause carries information.

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?

With no output schema, the description correctly compensates by describing the ScanResult contents, which is the key missing piece. For a simple 3-parameter read-only scanner this is close to complete; only the BLOCK-decision semantics and input size limit are left unmentioned.

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% — all three parameters (text, blockOnAny, minEntropy) are documented in-schema with defaults. The description adds nothing about parameter effects (e.g. what entropy threshold actually filters out), so baseline 3 applies.

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?

States a specific verb and resource: 'Scan text for leaked credentials, API keys, tokens, and other secrets.' The scope (secrets/credentials) is distinct from the PII-flavored sibling scan_pii, but the description never names that sibling, so differentiation is implicit rather than explicit.

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 only implied by the purpose statement — an agent can infer 'use this when text may contain secrets.' There is no explicit guidance on when to prefer scan_pii, check_prompt_injection, or detect_obfuscation instead, and no stated prerequisites, so the agent must work it out from sibling names.

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