Conciseness

Commands and tables are tight and operational, but the body restates the frontmatter description ('A skill for performing AI code review where OCR provides deterministic engineering...') and opens with maintenance meta-commentary about mirroring the canonical skill — minor instances of over-explanation that could be trimmed, matching anchor 4 rather than the every-token-earns-its-place anchor 5.

Actionability

Fully executable, copy-paste-ready commands throughout: 'ocr delegate preview --format json', fully-flagged git diff/show commands per mode, a common-invocations table covering workspace/range/commit cases, exact output-field descriptions, and a concrete comment schema table. Specific examples cover the common cases — anchor 5.

Workflow Clarity

Steps 1–7 are clearly sequenced with explicit validation checkpoints and error-recovery feedback loops: per-file checklist with 'reviewed' or 'skipped with a concrete reason', 'If Git fails or times out, retry or record skipped with the error', 'Check unexpectedly empty output against a fresh preview', mandatory coverage accounting before reporting, and a precise unknown-flag fallback with 'Do not retry without the flag for any other error'. This matches anchor 5 — the batch-coverage validation also satisfies the batch-operation cap.

Progressive Disclosure

The single-file body is well organized (numbered workflow, sub-command and flag tables, Gotchas, troubleshooting sections) with no nested references and nothing clearly orphaned. The flags/sub-command tables and the two long troubleshooting sections could arguably live in a one-level-deep reference file, leaving minor organization gaps — anchor 4 rather than the fully-split anchor 5.

Specificity

The description lists several concrete actions — 'perform the code review itself, using OCR only for deterministic engineering: file selection and rule resolution' — with a clear division of labor. Coverage has minor gaps (diff generation, output formatting, coverage reporting are not mentioned), so it fits anchor 4 rather than the comprehensive anchor 5.

Completeness

Both parts are present: a clear 'what' (delegation mode with OCR doing file selection and rule resolution) and an explicit 'Use when the host agent should drive the review with its own LLM capabilities' clause. The when-clause is meta/internal rather than a concrete user-facing trigger, matching anchor 4 ('when' could be more explicit) instead of 5.

Trigger Term Quality

'code review' and 'open-code-review' are natural trigger terms, but the rest leans on jargon ('deterministic engineering', 'LLM endpoint', 'host agent') and misses common user phrasings like 'review my changes/diff/PR'. The 'OCR' abbreviation also collides with optical character recognition, so this sits at anchor 3 (relevant keywords, missing variations) rather than 4.

Distinctiveness Conflict Risk

It occupies a clear niche (OCR delegation mode) tied to a specific tool, but generic 'code review' requests could pull this in when a plain review skill is intended, and 'OCR' is ambiguous with optical character recognition — mostly distinct with minor overlap risk (anchor 4), not the minimal-risk anchor 5.