hns-lsel-applier
Local Self-Evolution Loop (LSEL) APPLY engine — the playback-only consumer of approved decision.json records that drives `.moai/hooks/lsel-apply.sh` for the…
AI text humanization and 윤문 (post-editing) specialist that detects and removes AI tells while preserving meaning, facts, and figures. Covers Korean, English, Japanese, and Chinese with a shared severity model (S1/S2/S3), quality grades (A/B/C/D), and 30%/50% over-editing
$ npx -y skills add modu-ai/moai-adk --skill moai-domain-humanize --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/moai-domain-humanizeContext preview
The summary Claude sees to decide when to auto-load this skill.
AI text humanization and 윤문 (post-editing) specialist that detects and removes AI tells while preserving meaning, facts, and figures. Covers Korean, English, Japanese, and Chinese with a shared severity model (S1/S2/S3), quality grades (A/B/C/D), and 30%/50% over-editing
name: moai-domain-humanize description: > AI text humanization and 윤문 (post-editing) specialist that detects and removes AI tells while preserving meaning, facts, and figures. Covers Korean, English, Japanese, and Chinese with a shared severity model (S1/S2/S3), quality grades (A/B/C/D), and 30%/50% over-editing guardrails. Use to make AI-generated text read as human-authored without changing what it says (de-ai, naturalness pass). when_to_use: > Use for AI-text humanization and post-editing (윤문): detecting and removing AI tells across Korean, English, Japanese, and Chinese, applying the S1/S2/S3 severity model and quality grades while preserving meaning, facts, and figures. license: Apache-2.0 compatibility: Designed for Claude Code allowed-tools: Read, Write, Edit, Grep, Glob user-invocable: false metadata: version: "1.3.0" category: "domain" status: "active" updated: "2026-07-24" tags: "humanize, ai-tell, 윤문, post-edit, naturalness, multilingual, copy" # MoAI Extension: Progressive Disclosure progressive_disclosure: enabled: true level1_tokens: 100 level2_tokens: 5000
Post-editing specialist that removes "AI tells" from generated text and rewrites it to read as human-authored, while preserving meaning. This is the **editing** counterpart to text generation: it does not write new content, it refines how existing content is said. Covers Korean, English, Japanese, and Chinese, across two genre surfaces: **prose** (columns, reports, blog posts, formal documents) and **marketing copy** (headlines, CTAs, landing pages, brand storytelling, slide titles). Each language module carries a prose catalogue and a copy-layer catalogue; the shared machinery below (severity model, dual grading, mode-specific guardrails) applies uniformly.
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1. **Meaning preservation is the top rule.** Facts, numbers, statistics, named entities, quotations, citations, and the author's stance/certainty stay intact. Any meaning drift forces a rollback. In copy mode, "meaning" is defined by the fact anchors plus the core promise/benefit — see the copy-mode guard below. 2. **Evidence-based edits only.** Every change must trace to a detected tell on a specific span. Stylistic "improvements" unconnected to a catalogued tell are themselves an over-editing signal and are forbidden. 3. **Genre and register preservation.** Humanize *within* the source register — academic stays academic, casual stays casual. Never push formal text into slang or vice versa. Copy and slide genres apply their own structural rules (noun-phrase title boundaries, appeal-vs-informational voice) defined in each module's copy layer. 4. **Over-editing prevention.** In prose mode, flag at >30% change (WARN) and halt at >50% change (forced stop / human review) — above 50% you are regenerating, not humanizing. In copy mode, the change-rate guard is REPLACED by the fact-anchor preservation guard (see Over-Editing Guardrails below).
Two operating genres select which guardrail and grading table apply. Default from the text's genre; an explicit user instruction overrides.
| Mode | Genres | Over-editing guard | Grading table | |------|--------|--------------------|---------------| | **Prose mode** (default) | column, report, blog, formal/official document | Change-rate guard (WARN >30%, HALT >50%) | Prose-mode grades | | **Copy mode** | marketing copy, headline, CTA, landing page, brand story, slides | Fact-anchor preservation guard | Copy-mode grades |
Return two things:
1. **The humanized text.** 2. **A short change report**: categories hit (with counts), the final quality grade (A/B/C/D), and — in prose mode — the estimated percent changed. When a guardrail fires, state it explicitly (prose mode: WARN at >30%, HALT at >50%; copy mode: any fact-anchor loss).
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Each tell carries one severity tier. Detectors gate by occurrence count and overlap, because a single tell rarely proves AI authorship — confidence comes from clustering.
| Tier | Name | Rule | |------|------|------| | **S1** | Decisive | A single occurrence strongly confirms AI authorship → remove on first occurrence. | | **S2** | Strong | Acceptable at 1–2 instances → remove at 3 or more. | | **S3** | Weak | Problematic only when overlapping other tells → downgrade-only contributor. |
Graded **after** the rewrite. The genre mode selects the table: prose mode grades on residual tells plus change rate; copy mode grades on residual S1 plus fact-anchor integrity, with NO change-rate band.
Residual S1/S2 counts plus improvement % (= proportion of detected tells removed without introducing new ones).
| Grade | Criteria | Action | |-------|----------|--------| | **A** | 0 residual S1, ≤2 residual S2, ≥70% improvement | Pass — reads as human-authored | | **B** | 0 residual S1, ≤4 residual S2, ≥50% improvement | Pass — minor polish remains | | **C** | 1–2 residual S1, OR <50% improvement, OR over-edit WARN (>30%) | Trigger a second pass | | **D** | ≥3 residual S1, OR over-edit HALT (>50%), OR meaning drift detected | Request human review; do not auto-ship |
Residual S1 (including the module's copy-layer S1 tells), fact-anchor integrity, and self-verification — no change-rate band, because a legitimate headline rewrite routi
Agentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Single Go binary, 16 languages, zero deps.
Repo: modu-ai/moai-adk
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