Conciseness

The body is lean — a one-sentence scope statement, a compact API-generation table, one code example per concept, and gotcha lists that carry non-obvious information (Y-axis flip, bottom-left origin) with zero explanation of concepts Claude already knows; version numbers appear only within the modern-vs-legacy "Two API Generations" section, so they read as an old-patterns distinction rather than padding.

Actionability

The RecognizeTextRequest snippet is copy-paste ready (imports through topCandidates) and coordinate conversion gives exact code plus the flip formula, but the Core ML section is steps-only ("Compile model... Wrap with CoreMLModelContainer... or custom Core ML classification request") with no executable code — the 4 anchor's "minor gaps".

Workflow Clarity

"Route by Task" provides unambiguous task-to-reference routing, the Review Checklist supplies verification checkpoints, and Core ML is a clear 3-step sequence; however, the build paths lack explicit validate/verify steps, keeping it below the 5 anchor's feedback loops.

Progressive Disclosure

The SKILL.md is overview-only with two clearly signaled, one-level-deep references (both verified to exist at references/vision-requests.md and references/visionkit-scanner.md), each announced twice via task-based routing and a References list, with full implementation patterns correctly deferred to the bundle files — a direct match for the 5 anchor.

Specificity

"Builds or reviews iOS computer-vision features... including OCR, barcode and document scanning, face/object detection, segmentation, tracking, and Core ML inference" lists six-plus concrete capabilities in third-person voice, comprehensively covering the Vision framework domain — matching the 5 anchor rather than 4, where only minor gaps would exist.

Completeness

It explicitly answers both what (the enumerated capability list) and when ("Use for Vision requests, live DataScanner flows, or Vision/Core ML integration") with concrete trigger phrases, matching the 5 anchor exactly.

Trigger Term Quality

Natural phrases users would say — "OCR", "barcode", "face detection", "document scanning", "Vision requests", "DataScanner" — are present, but common synonyms like "text recognition", "image recognition", or "pose detection" are missing, so it falls short of the 5 anchor's comprehensive synonym coverage.

Distinctiveness Conflict Risk

The niche is clearly Apple's Vision/VisionKit frameworks with framework-specific triggers ("Vision requests", "DataScanner"); the only conceivable overlap is a dedicated Core ML skill, but "Vision/Core ML integration" scopes it, making the 5 anchor the best fit.