Conciseness

The body is lean, procedural, and entirely operational — iron rules, setup steps, per-route procedures, gate exit-code handling, and a result contract, with zero explanation of concepts Claude already knows. Every section earns its tokens; no padding is detectable. This matches the 'lean and efficient; every token earns its place' anchor and clearly exceeds level 4, which tolerates trimmable over-explanation.

Actionability

Commands are concrete and near copy-paste ready: exact absolute script paths ('python3 "${SKILL_ROOT}/scripts/verify_gates.py" --before "$RUN_DIR/01_input.txt" ... --json'), quoting rules, TAG generation via 'python3 -c "import secrets;print(secrets.token_hex(2))"', and exit-code semantics with prescribed responses. However, '$RUN_DIR' is used in commands but never assigned anywhere — step 3 describes the directory layout ('_workspace/YYYY-MM-DD-NNN-TAG/01_input.txt') without exporting the variable — leaving a minor gap that keeps it below 'fully executable; copy-paste ready' (level 5).

Workflow Clarity

Light/Standard/Heavy are clearly sequenced from setup through finalize, anchored by an explicit validation gate with per-exit-code recovery ('exit 2: 결과 채택 금지... 1회 재실행... 재차 exit 2면 hold_and_report'), rollback on >50% change rate, re-running gates after finalize, and a max-3-rounds loop with escalation to human review. This is the level-5 anchor: explicit validation steps, feedback loops, and error-recovery paths for a destructive/batch-capable operation.

Progressive Disclosure

Structurally the body does the right thing: it is a concise overview pointing one level deep to clearly signaled files ('references/quick-rules.md', 'references/diagnosis-rules.md', 'references/roles/{diagnostician,monolith,finalizer}.md') and keeps bulk detail out of SKILL.md. However, scoring against the actual bundle, the entire references/ directory is missing — none of the five referenced files exist (only scripts/ is present, and verify_change_rate.py is never referenced). The navigation chain leads to nonexistent resources, so disclosure cannot score as 'good structure' (4) or 'clear overview with well-signaled one-level-deep references' (5); it sits at 'some structure' with a broken reference chain.

Specificity

The description lists multiple concrete actions ('진단·윤문·검증한다' — diagnose, polish, verify), names specific pattern categories ('번역투, 기계적 병렬, 관용구, 피동, 접속사, 균일한 리듬 등 10대 카테고리 85개 패턴') and defines three execution routes (light·standard·heavy). This matches the 'multiple specific concrete actions; comprehensive coverage' anchor and exceeds the level-4 anchor, which allows coverage gaps — none are evident here.

Completeness

It explicitly answers both what ('AI가 쓴 한글 텍스트를 사람이 쓴 글처럼 진단·윤문·검증한다') and when ('"AI 티 없애줘"... 요청에 사용한다'), and additionally states when not to use it ('단순 맞춤법 교정, 번역, 사실이나 내용을 추가하는 재작성에는 사용하지 않는다'). This is the level-5 anchor verbatim in structure (clear what + explicit trigger phrases) and goes beyond it with exclusion guidance.

Trigger Term Quality

It provides comprehensive natural trigger phrases users would actually say: '"AI 티 없애줘", "AI 윤문", "사람이 쓴 것처럼", "번역투 고쳐", "정밀 모드", "2차 윤문", "이 문단만 다시", "humanize Korean"' — covering Korean colloquial phrasings plus the English skill name as a synonym. This matches the 'comprehensive coverage of natural terms including synonyms' anchor; the level-4 anchor ('a few natural terms missing') does not apply since no obvious variation is absent.

Distinctiveness Conflict Risk

It occupies a clear niche (humanizing AI-generated Korean text) with distinct triggers, and the explicit exclusions for spell-checking, translation, and content-adding rewrites sharply reduce overlap with adjacent editing/translation skills. This matches 'clear niche with distinct triggers; minimal conflict risk'; the level-4 anchor's 'minor overlap risk' would apply only without the exclusion clause.