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gridwork-aiact

gridwork-aiact

by thegridwork
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

scan_project

Detect AI system usage in a project directory and generate an EU AI Act compliance report that classifies risk level and identifies compliance gaps.

Instructions

Scan a project directory for AI system usage and generate an EU AI Act compliance report. Detects LLM APIs (OpenAI, Anthropic, Google, Mistral, etc.), ML frameworks (PyTorch, TensorFlow, scikit-learn), computer vision, NLP, embeddings, and more. Classifies risk level and identifies compliance gaps against the August 2, 2026 deadline.

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": {
      "path": "<path>"
    },
    "name": "scan_project"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesAbsolute path to the project directory to scan
formatNoOutput formatmarkdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. While it explains what the tool detects and outputs, it does not mention whether the operation is read-only, requires network access, or has any side effects. This is a significant gap for a tool that performs a scan.

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 concise and well-structured: three sentences that first state the purpose, then list detection capabilities, and finally describe the output. Every sentence adds value without extraneous information.

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?

Given the absence of an output schema, the description should provide more detail about the report structure or what the tool returns. It mentions risk level and compliance gaps but not whether it returns a file or response object. For a compliance report generator, this is incomplete.

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 coverage is 100%, so the baseline is 3. The description does not add any additional detail about the parameters beyond what the schema already provides. It does not explain the effect of different format choices or how the path should be specified beyond 'absolute path'.

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?

The description clearly states the tool's purpose: scanning a project directory for AI system usage and generating an EU AI Act compliance report. It lists specific items detected (LLM APIs, ML frameworks, etc.) and outputs, which distinguishes it from siblings like quick_check or generate_inventory.

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?

The description provides clear context on when to use this tool (for comprehensive scanning and compliance reporting) but does not explicitly mention when not to use it or compare to alternative sibling tools. The context is sufficient though not exhaustive.

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

Deploy Server

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