check_specific

Run specific validation checks on a TwinCAT file.

SERVERTwinCAT Validator MCP Server SOURCEagenticcontrolio/twincat-validator-mcp

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade C, identity unverified Pull the record →

This record as markdown: /tools/agenticcontrolio-twincat-validator-mcp/check-specific.md

WHAT IT DOES

What check_specific does on TwinCAT Validator MCP Server

AI agents call check_specific to retrieve information from TwinCAT Validator MCP Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why check_specific is rated Low

This tool performs structural validation and code quality analysis on TwinCAT 3 XML files. It reads file content, applies deterministic validation rules from IEC 61131-3 OOP standards, and returns validation results. No data is modified, deleted, or executed—it is purely introspective. The sibling tools 'autofix_file' and 'generate_skeleton' perform writes, but 'check_specific' itself only examines and reports.

From the tool's definition Tool name 'check_specific' and description 'Run specific validation checks on a TwinCAT file' indicate querying/analysis of code quality without modification.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs check_specific safely

PolicyLayer is an MCP gateway: it sits between your AI agents and TwinCAT Validator MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For check_specific, this is the rule to start with:

check_specific Allowed

check_specific is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "check_specific": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect TwinCAT Validator MCP Server, apply this rule, and every check_specific call is checked against it from then on.

FAQ

Questions about check_specific

What does the check_specific tool do? +

Run specific validation checks on a TwinCAT file. It is categorised as a Read tool in the TwinCAT Validator MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on check_specific? +

Register the TwinCAT Validator MCP Server MCP server in PolicyLayer and add a rule for check_specific: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches TwinCAT Validator MCP Server. Nothing to install.

What risk level is check_specific? +

check_specific is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit check_specific? +

Yes. Add a rate_limit block to the check_specific rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block check_specific completely? +

Set action: deny in the PolicyLayer policy for check_specific. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides check_specific? +

check_specific is provided by the TwinCAT Validator MCP Server MCP server (agenticcontrolio/twincat-validator-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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