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diagnose_app_quality

Analyze UI quality of shadcn/Tailwind apps from code or URL. Identify issues, scores, and fix categories to plan improvements or export design debt context.

Instructions

Diagnose UI quality for an existing shadcn/Tailwind app from code or a public URL.

Returns on success: App-quality diagnosis V2 with scores, issues, evidence locations, affected files, confidence, effort estimates, fix categories, and app graph summary.

Use this tool: before planning UI fixes, exporting a registry, or giving an AI editor context on real app design debt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetNoLocal path or public URL to scan. Defaults to the current project root.
maxFilesNoMaximum source files to scan.
Behavior4/5

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

With no annotations, the description carries the full burden. It details the return value comprehensively (scores, issues, evidence locations, etc.) and implies a read-only operation by diagnosing from code/URL, but does not explicitly state it is non-destructive.

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?

Three sentences, each earning its place: purpose, output details, and usage context. Front-loaded and no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a diagnostic tool with 2 parameters and no output schema, the description covers purpose, usage, and output comprehensively, leaving no critical gaps.

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 descriptions for both parameters. The description does not add significant meaning beyond the schema, which is baseline 3.

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 clearly states the verb 'diagnose', resource 'UI quality for a shadcn/Tailwind app', and scope 'from code or a public URL', distinguishing it from siblings like 'run_audit' or 'analyze_design'.

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 explicitly says 'Use this tool: before planning UI fixes, exporting a registry, or giving an AI editor context on real app design debt', providing clear when-to-use guidance, though it does not mention when not to use or alternatives.

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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