lazymac-mcp

prompt_shield

Detect prompt injection attempts, jailbreak techniques, and PII in LLM inputs to enhance security and prevent unauthorized access.

Instructions

Prompt injection / jailbreak / PII detection for LLM inputs

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "prompt_shield"
  }
}

Input Schema

Name	Required	Description	Default
`params`	No	Free-form params object — passed as query string for GET, JSON body for POST

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Apr 15, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the tool's function but lacks behavioral details such as input/output format, performance characteristics, rate limits, or error handling. This is inadequate for a tool with a free-form params object and no output schema.

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, efficient phrase that front-loads the core purpose without unnecessary words. Every part earns its place by concisely stating the tool's function.

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?

Given the complexity (security detection tool), lack of annotations, no output schema, and a free-form params object, the description is incomplete. It fails to provide sufficient context for safe and effective use, such as expected input structure or result interpretation.

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 input schema has 100% description coverage, documenting a free-form params object. The description does not add meaning beyond the schema (e.g., example parameters or constraints), so it meets the baseline of 3 for high schema coverage without compensating value.

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 purpose as detecting prompt injection, jailbreak attempts, and PII in LLM inputs. It uses specific verbs ('detection') and identifies the target resource ('LLM inputs'), but does not differentiate from sibling tools, which appear unrelated (e.g., ai_budget_planner, email_validator).

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 guidance is provided on when to use this tool versus alternatives. The description implies usage for security/validation of LLM inputs, but lacks explicit context, prerequisites, or comparisons to other tools (e.g., text_analysis or other validation tools).

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