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Nodeblue-AI

bridge-mcp-server

by Nodeblue-AI

correlate_projects

Maps Ignition OPC tags to L5X PLC tags via OPC item path normalization, returning matched and unmatched tags to identify integration gaps.

Instructions

Build a full correlation map between an Ignition project and an L5X PLC project.

Walks all Ignition OPC tags, maps each to its L5X counterpart via OPC item path normalization, and returns matched pairs plus unmatched tags on both sides.

Args: ignition_path: Path to Ignition project directory or .zip export. l5x_path: Path to Studio 5000 .l5x file. mapping_file: Optional JSON file with explicit tag mappings (overrides convention).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
l5x_pathYes
mapping_fileNo
ignition_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.4.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does this well by explaining that it walks all Ignition OPC tags, normalizes OPC item paths, maps them to L5X counterparts, and returns both matched and unmatched sets. It does not mention side effects or failure modes, but the core behavior is transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose, followed by behavioral detail and the Args section. The Args block is justified because the schema lacks property descriptions, and the prose is efficient overall, though the first two sentences are slightly redundant.

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?

For a file-analysis tool that already has an output schema, the description covers the purpose, matching strategy, inputs, and output categories. The main gaps are the exact JSON structure expected for mapping_file and an explicit note that the operation is read-only, but these are minor relative to the given context.

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

Parameters5/5

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

Schema description coverage is 0%, so the description fully compensates by documenting each parameter in plain language. It explains ignition_path can be a directory or .zip export, l5x_path is a Studio 5000 .l5x file, and mapping_file is an optional JSON override. This adds real meaning beyond the bare schema property definitions.

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 opens with a specific verb and resource: 'Build a full correlation map between an Ignition project and an L5X PLC project.' It then details the algorithm and output, which clearly distinguishes it from the sibling find_unmapped_tags, since this tool returns both matched pairs and unmatched tags on both sides.

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 clearly conveys that this tool is for full correlation mapping and that it reports matched and unmatched tags on both sides, giving an agent a clear sense of when to choose it. It does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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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