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scout_design_audit

Audits a page's computed styles to uncover measurable design defects and craft improvement suggestions, covering contrast, target sizes, overflow, focus indicators, and visual consistency.

Instructions

Computed-style design audit of the current page — a design connoisseur's read WITHOUT screenshots. Measurable defects (⚠): WCAG contrast, tiny targets, clipped text, aspect-distorted images, horizontal overflow, missing keyboard-focus indicators (sampled with real Tab presses). Craft suggestions (→): line measure and line-height rhythm, spacing-scale adherence, typography entropy, palette discipline (gray census, accent hue families, pure-#000 body text), elevation/control consistency, heading structure, indistinguishable links, and AI-slop tells (gradient text, glassmorphism, side-stripe borders, neon glows, violet gradients, identical card grids). Ends with a SYSTEM SUMMARY of design-system coherence. Run once per representative page; the → tier is improvement feedback — file genuine opportunities as ux-polish findings with the concrete numbers, not just defects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sessionNoTarget this session directly instead of the active one — pass it explicitly when dispatching to MULTIPLE sessions in one turn (e.g. two scout_click calls with different `session`), which then run CONCURRENTLY rather than queueing. Omit for single-session sequential use.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0

TDQS

A4.1/5.0
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 and does a good job: it declares the audit is computed-style without screenshots, samples keyboard focus with 'real Tab presses', and lists both measurable defects and craft suggestions. It does not address side effects or permissions, but as a read-only audit the implied behavior is clear.

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 long but densely informative, with clear structure: purpose, defect types, suggestion types, summary, and usage note. It front-loads the core identity and every subsequent clause adds practical detail. A little trimming would be possible, but the length serves the complexity of the tool.

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?

Given the tool has no output schema and no annotations, the description compensates well by enumerating what the audit detects, the structure (defects vs. suggestions vs. system summary), and how to use the results. It does not specify the exact return format, but the content coverage is sufficient for an agent to invoke it 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?

The only parameter, session, is already fully documented in the input schema with clear guidance on when to pass it explicitly. The description adds no additional parameter semantics, which is acceptable because schema coverage is 100%.

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: a 'computed-style design audit of the current page', and explicitly distinguishes itself with 'WITHOUT screenshots'. It enumerates distinct audit categories (WCAG contrast, tiny targets, clipped text, etc.), making its purpose unmistakable compared to siblings like scout_screenshot or scout_scan.

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?

It gives clear usage context: 'Run once per representative page' and instructs that improvement-tier findings should be filed as ux-polish findings with concrete numbers rather than just as defects. It does not explicitly name alternative tools or exclusion criteria, but the context is specific enough to guide correct invocation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.