moai-domain-humanize
**moai-domain-humanize** is a post-editing tool that removes artificial language patterns from AI-generated text across Korean, English, Japanese, and Chinese while preserving factual accuracy and authorial intent. Use it to refine machine-generated content into natural-sounding prose, with built-in safeguards that warn when more than 30% of text changes and stop at 50% to prevent over-editing.
git clone --depth 1 https://github.com/modu-ai/moai-adk /tmp/moai-domain-humanize && cp -r /tmp/moai-domain-humanize/.claude/skills/moai-domain-humanize ~/.claude/skills/moai-domain-humanizeSKILL.md
# moai-domain-humanize 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. --- ## Quick Reference ### Operating Principles (4) 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). ### Genre Mode Selection (Prose vs Copy) 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 | ### Processing Mode Selection (Fast / Strict) - **Fast mode** (default, up to ~5,000 chars): a single pass — detect, rewrite, self-verify against the meaning-preservation checklist. - **Strict mode** (long or high-stakes text, or when requested): separate stages — detect → surgical rewrite → content-fidelity audit (facts/figures/stance unchanged) → naturalness review. Re-run a second pass when the result lands at Grade C. ### Output Contract 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). --- ## Common Severity Model (shared by all 4 languages) 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. | ## Common Quality Grades (shared by all 4 languages — dual tables) 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. ### Prose-Mode Grade Table 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 | ### Copy-Mode Grade Table 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 routinely changes most of its characters while preserving every anchor. | Grade | Criteria | Action | |-------|----------|--------| | **A** | 0 residual S1, 0 fact-anchor loss, self-verification passed | Pass — ships as human copy | | **B** | 0 residual S1, ≤1 conservative fact-anchor concern | Pass with an explicit note | | **C** | 1 residual S1, OR self-verification partially failed | Trigger a second pass | | **D** | 2+ residual S1, OR 2+ fact-anchor losses | Request human review; do not auto-ship | Hard rule (both modes): any residual S1 caps the grade at C; any meaning-distortion flag forces D. S3 tells affect the grade only when ≥3 of them overlap and reinforce an S1/S2 finding. ### Over-Editing Guardrails (shared) **Prose mode — change-rate guard.** Change rate = the proportion of the text altered; target band ~5–30%. - **>30% changed → WARN.** Surface a caution and cap at Grade C until each edit is justified by a detected tell. Note: padding-removal legitimately shrinks text, so a length drop alone is not a violation — flag when meaning-bearing spans are altered. - **>50% changed → HALT.** Stop and require h
Claude Code upstream change tracker -> moai-adk update plan + docs sync workflow (dev-only). Tracks new CC release notes, classifies changes by impact tier, cross-references official docs, generates update plan at .moai/research/ or .moai/specs/, and synchronizes docs-site 4-locale + README. NOT distributed to user projects.
GitHub Workflow - Manage issues and review PRs with Agent Teams (dev-only). NOT distributed to user projects.
MoAI-ADK production release via Enhanced GitHub Flow (CLAUDE.local.md §18). Creates release/vX.Y.Z branch, version bump, CHANGELOG (bilingual), PR to main, merge commit (NOT squash), then scripts/release.sh for tag + GoReleaser. Hotfix support via --hotfix flag. All git operations delegated to manager-git. Quality failures escalate to expert-debug. NOT distributed to user projects (dev-only).
Run the 7-phase /moai brain ideation workflow to convert ideas into validated proposals
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Scan codebase and generate architecture documentation in codemaps/
Analyze test coverage, identify gaps, and generate missing tests
Hybrid design workflow — Claude Design import (path A) or code-based brand design (path B)