ai-writing-humanizer

name	ai-writing-humanizer
description	Humanize a document by removing AI-writing patterns via a multi-agent workflow (analyze → revise → adversarial review → loop-until-clean). Use when the user asks to "humanize", "de-AI", "remove AI tells", or "review for AI writing" on a file.
author	Raul
version	1.0.0
tags	["writing","humanizer","ai-detection","editing"]
level	user

AI Writing Humanizer (workflow launcher)

This skill launches a multi-agent Workflow that humanizes a document: it analyzes AI-writing tells across three lenses, rewrites fidelity-first, then runs four adversarial reviewers (fidelity / residual-tells / quality-voice / gap) and loops until clean. It auto-fixes critical/high issues and surfaces medium/low (and anything the fidelity guard blocks) as prioritized tasks.

A full pass dispatches many agents and is token-intensive. Before running, confirm with the user: which file, and whether to proceed.

Steps

1. Resolve the target. Get the file path from the user. If they pasted text instead, write it to a scratch file first (the engine works on a document). Set ROOT="${CLAUDE_PLUGIN_ROOT}/skills/ai-writing-humanizer".

2. Pre-scan (deterministic). Run:

   node "$ROOT/workflows/prescan.js" "<file>" "$ROOT/patterns/patterns.json" "$ROOT/config/default.config.json"
   

   Capture stdout as mechanicalFindings (a JSON array).

3. Assemble args. Read <file> → text; read $ROOT/patterns/patterns.json → patterns; read $ROOT/prompts/analysis-prompt.md, suggestion-prompt.md, verification-prompt.md → prompts = { analysis, suggestion, verification }; read $ROOT/config/default.config.json → config.

4. Run the engine:

   Workflow({
     scriptPath: "$ROOT/workflows/humanize.js",
     args: { text, patterns, prompts, mechanicalFindings, config }
   })
   

5. Write the revision. Write the returned revisedText to a sibling <name>.humanized.<ext> (never overwrite the input). Show the user a diff of <file> → the revision.

6. Print the on-screen report (no file). Two sections, grouped by priority:

   • ✔ Fixed — counts from fixedByPriority.
   • ⚠ Still flagged — the residual findings (span + why), grouped critical/high/medium/low. Include the fidelity and quality verdicts.

7. Create residual tasks. For each finding in residual, create ONE task-list entry, its priority = the finding's priority. If residual is empty, create no tasks — say it's clean.

Fallback (no Workflow tool)

If the Workflow tool is unavailable in this harness, do not fail. Instead run the same phases inline: dispatch the 3 analyze lenses and 4 reviewers as subagents (Agent tool), do the revise step yourself, and apply the same loop-until-clean logic, then produce the same report + tasks.