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SolidworksMCP-python

SolidworksMCP-python

by andrewbartels1
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

analyze_macro

Evaluate macro code complexity and dependencies to identify optimization opportunities, aiding maintenance and performance.

Instructions

Analyze a macro for complexity, dependencies, and optimization opportunities.

This tool provides insights into macro structure and performance to help with optimization and maintenance.

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": {
      "input_data": "<input_data>"
    },
    "name": "analyze_macro"
  }
}

Input Schema

NameRequiredDescriptionDefault
input_dataYesThe input data value.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations exist, so the description carries full burden. It mentions providing insights into structure and performance but does not disclose whether the tool is read-only, requires specific permissions, or has side effects. The behavioral traits are vague.

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, no wasted words, front-loaded with the core purpose. Efficient and well-structured.

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?

Given the complexity (nested input schema, output schema, many siblings), the description is too generic. It does not explain output contents, analysis types, or depth options, leaving significant gaps for an agent to use the tool correctly.

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% with parameter descriptions in the schema itself. The description adds no additional meaning beyond 'analyze a macro', missing context on how to specify the macro (e.g., file path vs. content). Baseline score applies due to high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool analyzes macros for complexity, dependencies, and optimization, with a verb 'Analyze' and resource 'macro'. It distinguishes from siblings like 'optimize_macro' by focusing on analysis rather than modification, but does not explicitly name alternatives.

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?

No guidance on when to use this tool versus siblings such as 'optimize_macro' or 'execute_macro'. The description implies analysis precedes optimization but provides no explicit context or exclusion criteria.

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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