Essay Humanizer (corpus-informed)

Rewrites AI-generated argumentative/academic essays toward human baseline style informed by CAWSE (M/D bands) LOCNESS, and contrast with DeepSeek-generated counterparts. Ships with a fine-tuned LoRA adapter (9.3 MB) and inference script.

Skill contract

Requirements: Apple Silicon macOS with Python 3.9+.

Quick Start

bash scripts/install_deps.sh          # one-time: installs deps + decodes adapter
python scripts/inference.py --file draft.txt   # adapter auto-decodes if not already done

Or from Python:

from scripts.inference import humanize
print(humanize("Your AI-drafted essay text here..."))

Weighted pattern table (descending priority)

When humanizing, address higher-weight rows first. Weights are data-driven from corpus analysis (Mann-Whitney); zero-weight rows were not statistically significant.

Syntactic complexity (MDD / ADD advisory)

Human Merit / Distinction-range writing in CAWSE often shows variable mean dependency distance (MDD); AI prose may cluster more tightly. When humanizing:

• Reference MDD means from analysis: human ~2.333775514332394, AI ~2.4553791855163483.
• Variance ratio (human/AI) ~1.7153931408079544: prefer natural mix of shorter and longer dependency links, not uniformly smoothed sentences.
• Avoid flattening every sentence to minimal dependency length; that can read as a different kind of machine polish.

Mandatory rule (orchestrator)

1. Output continuous prose suitable for submission (no chat-signoffs, no "hope this helps").
2. Plain text only for math if any — no raw $$ LaTeX unless user explicitly requests LaTeX.
3. Preserve author stance and citations if present; do not fabricate references.

Hosted HTTP API (optional, for non-Mac or remote use)

For non-Apple-Silicon machines or multi-user deployments, run the optional FastAPI server on a Mac host and connect via HTTP/OpenAPI:

1. Install: pip install fastapi uvicorn[standard]
2. Run: uvicorn api.main:app --host 0.0.0.0 --port 8765 (set HUMANIZE_API_KEY env var for auth)
3. Point MCP / OpenAPI tools at https://\x3Cyour-host>/openapi.json
4. Call POST /v1/humanize with JSON {"text":"..."} (+ Authorization: Bearer …)

See references/hosted_api.md for details.

References

• references/patterns.md — 24 pattern details with detection/fix hints
• references/training.md — full training pipeline
• references/hosted_api.md — HTTP API / MCP tool linking