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audit_ios_screen

Read-onlyIdempotent

Audits a rendered iOS screen's accessibility snapshot to score touch-target sizes, color contrast, and visual rhythm, surfacing actionable design flaws.

Instructions

Audit a rendered iOS screen from a view-hierarchy/accessibility snapshot (and optional screenshot). Alias of audit_screen with platform:"ios". Call with no arguments for the expected snapshot shape. Call with {elements:[{label,rect:{x,y,w,h},role,fontPt,fgColor,bgColor}],viewport:{w,h}} to score 44×44pt touch targets, contrast (with iOS secondaryLabel/tertiaryLabel treated as platform-standard — warn not fail), and visual rhythm (alignment, gap consistency, optical balance) in points. Same return shape as audit_page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profileNoTaste profile owning the binding. Omit to search all stored profiles for one bound to the project.
projectNoProject identifier — resolves a saved taste surface binding (see bind_taste_surface). When the binding carries design_notes and a screenshot is passed, the screenshot's pixels verify the color-scheme notes; results gain note_assessments.
elementsNoElements captured from the rendered screen via an accessibility/view-hierarchy snapshot
viewportNoScreen size in pt (iOS) or dp (Android) at capture time, e.g. {w:393,h:852} iPhone 15, {w:412,h:915} Pixel
screenshotNoOptional base64 PNG of the screen, for the caller's reference. Geometry is scored from the snapshot, not decoded pixels.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.2.9

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/destructive annotations, the description reveals what the audit will score (44×44pt targets, contrast, visual rhythm), that iOS semantic colors like secondaryLabel/tertiaryLabel are treated as platform-standard with warn-not-fail behavior, and that screenshot is optional. This materially clarifies behavior.

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 compact, front-loaded with the core purpose, and every sentence carries distinct value: purpose, alias relationship, no-args usage, example payload structure, scoring criteria, and return shape reference. No redundant filler.

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 read-only analysis tool with rich schema coverage and annotations, the description fully covers what inputs are needed, how to invoke it, what scoring dimensions are inspected, and what return shape to expect. The no-arguments behavior and alias note make it safe for an agent to use without additional research.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful usage semantics by showing an expected elements payload and viewport shape, and clarifying that the screenshot is optional. It also gives key scoring semantics such as point-based dimensions and warn-not-fail color handling.

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 tool audits a rendered iOS screen from a view-hierarchy/accessibility snapshot, and explicitly identifies it as an alias of audit_screen with platform 'ios'. This distinguishes it from broad siblings like audit_page and audit_screen while also signaling the return shape.

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 gives clear usage context: call with no arguments to see the expected snapshot shape, or call with elements and viewport to perform scoring. It also names the alias relationship and the same return shape as audit_page. It does not explicitly call out alternatives or exclusions, but the iOS scope provides adequate guidance.

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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