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OpenFab MCP

by HB-0921
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

fanuc_lint_ls

Lint FANUC LS source code offline and receive structured diagnostics, helping you identify syntax issues before deploying robotic programs.

Instructions

Lint FANUC LS source offline and return structured diagnostics.

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": "fanuc_lint_ls"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathNo
textNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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 add useful context by stating the operation is offline and returns structured diagnostics, but it does not discuss side effects, permissions, failure modes, or limitations.

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, front-loaded sentence where each component adds value: action, resource, mode, and output. There is no redundancy or filler.

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?

An output schema exists, so omitting return-value details is acceptable, but the description fails to explain how the two optional inputs interact or when each should be used. Combined with zero annotations and zero schema descriptions, this leaves a significant gap in call construction.

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 description coverage is 0%, and the description never mentions the path or text parameters, their relationship, or which one should be supplied. The word 'source' is too generic to help an agent construct the correct invocation.

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 uses 'Lint' as a specific action and identifies the resource ('FANUC LS source'), the mode ('offline'), and the result ('structured diagnostics'). This clearly distinguishes it from siblings like fanuc_parse_ls and fanuc_generate_ls_draft.

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?

There is no guidance on when to use this tool versus fanuc_parse_ls or fanuc_generate_ls_draft, nor whether callers should provide path, text, or both. An agent would have to infer the usage context from the tool name alone.

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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