Conciseness

The body is noticeably verbose through systematic duplication: every sweep carries two overlapping bullet lists (e.g., Sweep 3's 'What to check: Features without benefits / Claims without consequences...' vs. 'Common So What failures: Feature lists without benefit connections...'), a per-sweep loop-back note that restates the return chain seven times, a ~50-line 'Copy Editing Checklist' that restates all seven sweeps nearly verbatim, and a word-replacement table ('Utilize→Use, Leverage→Use...') that duplicates the bundled references/plain-english-alternatives.md. This matches anchor 2 ('noticeably verbose; several unnecessary explanations or padded sections') — the duplicated material is domain-specific rather than concepts Claude already knows, so it is not the severe padding of anchor 1, but 'mostly efficient' (anchor 3) does not hold for a ~500-line body whose second half repeats its first.

Actionability

Guidance is fully executable for an instruction-only skill: two runnable commands with flags and expected outputs ('python3 scripts/readability_scorer.py --file draft.md' with '--json', 'python3 scripts/ai_content_detector.py draft.md --json'), numbered per-sweep processes, a concrete before/after example (❌ 'Our platform uses AI-powered analytics' → ✅ benefit-bridged rewrite), specific vague→specific replacement tables, symptom/fix problem patterns, and an output-artifacts table mapping requests to deliverables. It matches anchor 5 — copy-paste-ready commands with specific examples covering the common cases.

Workflow Clarity

The Seven Sweeps Framework is a clearly sequenced multi-step process with explicit checkpoints: each sweep ends with a return-loop instruction ('After this sweep: Return to So What, Voice and Tone, then Clarity'), Sweep 1 embeds a mechanical validation loop ('re-run the scorer; the Flesch score should improve, not regress'), and the collaborative workflow closes with 'Repeat until clean — Continue until a full sweep finds no new issues.' Editing is non-destructive and the AI-detector pre-check gates the workflow ('polishing AI mush produces polished AI mush'). This matches anchor 5: clear sequence, explicit validation steps, feedback loops, and a checklist.

Progressive Disclosure

Structure exists (clear section headers, one properly signaled reference: '[Plain English Alternatives](references/plain-english-alternatives.md)', and both scripts referenced with usage), but scored against the actual bundle it has real gaps: references/ai-detection-patterns.md exists in the bundle yet is never linked from SKILL.md — the AI-Pattern Check section runs the detector but does not point to the patterns file — and substantial content that belongs in reference files is inlined (the word-level 'Cut these/Replace these' tables duplicate plain-english-alternatives.md, and the full checklist section restates the sweeps). This matches anchor 3 ('some structure... content that should be separate is inline') rather than anchor 4, where most content would be appropriately placed.

Specificity

The description names the domain ('existing marketing copy') and a couple of generic actions ('edit, review, or improve'), plus a mechanism ('systematic approach to editing marketing copy through multiple focused passes'), but it never enumerates the concrete actions the skill performs (e.g., the seven sweeps: clarity, tone, proof, specificity, risk reduction). It matches anchor 3 ('names domain and 1-2 concrete actions, but not comprehensive') rather than anchor 4, which expects several specific actions listed; it is above anchor 2 because the domain and approach are clearly stated rather than minimal.

Completeness

Both parts are present: an explicit 'when' (twice — 'When the user wants to edit...' and 'Also use when the user mentions...') with concrete trigger phrases, and a 'what' ('provides a systematic approach to editing marketing copy through multiple focused passes'). It falls short of anchor 5 because the 'what' is a single high-level sentence rather than a concrete statement of what the skill actually does or produces; it is above anchor 4's typical weakness because the 'when' is highly explicit and specific.

Trigger Term Quality

The trigger list is comprehensive and natural: "'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' or 'copy sweep'" — these are exactly the synonyms and phrasings a user would say, covering review, edit, feedback, and proofreading verbs with variations. It clearly matches anchor 5 (comprehensive coverage of natural terms including synonyms); no file extensions are relevant to this domain, and the variation coverage exceeds anchor 4's 'good coverage, a few natural terms missing'.

Distinctiveness Conflict Risk

The niche is clear (editing existing marketing copy vs. writing new copy, which the related-skill table distinguishes), and most triggers are copy-specific. Minor overlap risk remains from generic phrases like 'polish this' and 'make this better,' which a user could say about non-marketing text (essays, emails, code docs), pulling in this skill for general proofreading. That matches anchor 4 ('mostly distinct; minor overlap risk with closely related skills') rather than anchor 5, whose triggers are unambiguous.