io.github.daedalusdevelopmentgroup/ddg-agent-services-mcp

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ddg_skill_safety_scan

Run a static safety scan on AI skill or workflow markdown to identify risks without executing code. Redacts secret-like evidence to protect sensitive information.

Instructions

Run the free static-only DDG AI skill/workflow safety scan.

The scan never executes submitted code and redacts secret-like evidence.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "skill_markdown": "<skill_markdown>"
    },
    "name": "ddg_skill_safety_scan"
  }
}

Input Schema

Name	Required	Default
`skill_markdown`	Yes
`label`	No	mcp-client-submission
`agent_id`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 23, 2026

TDQS

A3.8/5.0

Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that the scan never executes code and redacts secret-like evidence, providing key safety and privacy behaviors.

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, front-loaded with purpose, no wasted words. Highly efficient.

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

Completeness3/5

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

Missing parameter descriptions and usage prerequisites, but output schema exists and safety scan concept is simple. Adequate but not comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but description adds no explanation for the three parameters (skill_markdown, label, agent_id). Agent cannot infer their meanings from description alone.

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?

Description clearly states the tool runs a safety scan, with specific verb 'run' and resource 'DDG AI skill/workflow'. No sibling tool shares this purpose.

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?

Indicates the scan is static-only and never executes code, but does not explicitly state when to use this tool versus alternatives. However, sibling tools are distinct, so context is sufficient.

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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