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lady-logic

MMI Architecture Analyzer

by lady-logic

visualize_architecture

Generate interactive heatmap visualizations to analyze C# project architecture quality, showing dependencies, violations, and modularity scores with D3.js.

Instructions

Generate interactive architecture heatmap visualization with D3.js. Shows files as nodes colored by score (green=good, red=critical), dependencies as links, violations highlighted. Click nodes to see details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathYesPath to the C# project directory
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the visualization output and interactive features, but doesn't cover critical aspects like performance implications, data sources (e.g., whether it analyzes code in real-time or uses cached results), error handling, or system requirements. For a visualization tool with zero annotation coverage, this leaves the agent guessing about operational behavior.

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 efficiently structured in two sentences: the first covers the core functionality, and the second adds interactive details. It's front-loaded with the main action ('Generate interactive architecture heatmap visualization') and avoids unnecessary fluff. However, it could be slightly more concise by integrating the color coding into the first sentence.

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 tool's complexity (visualization with interactive features), no annotations, no output schema, and a simple input schema, the description is minimally adequate. It explains what the tool produces but lacks details on output format (e.g., HTML file, URL), error cases, or integration with sibling analysis tools. It meets basic requirements but leaves gaps for effective agent use.

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 description coverage is 100%, with the single parameter 'projectPath' fully documented in the schema as 'Path to the C# project directory.' The description adds no additional parameter context beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to.

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's purpose: 'Generate interactive architecture heatmap visualization with D3.js.' It specifies the visualization type (heatmap), technology (D3.js), and key elements (files as nodes, dependencies as links, violations highlighted). However, it doesn't explicitly differentiate from sibling tools like analyze_abstraction or analyze_cycles, which appear to be analysis tools rather than visualization tools.

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?

The description provides no guidance on when to use this tool versus alternatives. It mentions interactive features like clicking nodes for details, but doesn't specify use cases, prerequisites, or exclusions. Given sibling tools like analyze_abstraction that might provide complementary data, the lack of comparative context is a significant gap.

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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