AI Content Collaboration Workflow
An editorial playbook for deciding what humans must own, where AI may help, and how to keep AI-assisted content on-voice and honest.
Content & WritingIntermediate★ 867⑂ 120AI score 9/10Last updated: Sep 15, 2026
What it does
- Draws ownership boundaries: the "humans own, AI accelerates" keystone — AI may do research synthesis, outlines, first drafts, alternative phrasings, transcription, and at-scale QA flagging; humans must own editorial judgment, voice, fact verification, quote attribution, and final sign-off.
- Five hybrid workflow patterns: AI-first draft with heavy human edit; human outline + AI draft + human rewrite; AI as research assistant; human writes with AI as editor; AI-at-scale with human sampling — each with tradeoffs and selection criteria.
- Voice preservation tactics: voice guidelines as prompt context, canonical sample paragraphs as a voice anchor, mid-draft drift checks, a human-written final pass, and a reject-the-bland rule.
- AI slop prevention: what produces slop, what prevents it, and why readers sense it even when they can't name it.
- Tiered disclosure framework: always disclose / default disclose / generally unnecessary / clearly fine, plus concrete disclosure wording.
- Team calibration and an ethical floor: documented AI policy, calibration sessions, onboarding, intellectual-honesty principles, 11+ failure modes, and a 12-point workflow audit.
Who it's for
- Editorial leaders, content directors, content ops managers
- In-house teams whose AI-assisted output feels correct but generic
- Agencies running AI-assisted production across many writers
- Regulated or trust-sensitive orgs that need an explicit AI usage policy
Examples
- "Our blog reads the same as everyone else's since we adopted AI" → apply voice-preservation patterns and rewrite discipline to redesign the editing stage.
- "Should an expert-bylined newsletter disclose AI drafting?" → use the disclosure tiers to decide, then draft the disclosure line.
- "Eight writers, eight different AI habits" → produce a team AI policy (approved / permission-required / prohibited) plus a calibration cadence.
· · · Install guide · · ·
Try it now, no install
Paste this into Claude to use the skill without installing anything.
Read the instructions in this file and follow them to help me: https://raw.githubusercontent.com/rampstackco/claude-skills/HEAD/dist/codex/.agents/skills/ai-content-collaboration/SKILL.md What I want: (describe your task here)
If Claude can't open the link, open it yourself and paste the contents instead.
↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.
Install in the Claude app (no terminal)
- Download the ZIP with the button below.
- In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
- Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
Install in Claude Code
Let Claude do it — paste this into Claude Code
Install the skill I found on Claude Skill Mart. Copy the dist/codex/.agents/skills/ai-content-collaboration folder from the GitHub repo rampstackco/claude-skills into my ~/.claude/skills/rampstackco-ai-content-collaboration/. When it's done, tell me in one line what this skill can do.
Install with a command instead
git clone https://github.com/rampstackco/claude-skills.git /tmp/claude-skills && mkdir -p ~/.claude/skills && cp -r /tmp/claude-skills/dist/codex/.agents/skills/ai-content-collaboration ~/.claude/skills/⚠ This is a third-party skill. Check the source repository before installing.
- Open your terminal.
- Clone the repo:
git clone https://github.com/rampstackco/claude-skills.git - Create the skills directory:
mkdir -p ~/.claude/skills - Copy this skill over:
cp -r claude-skills/dist/codex/.agents/skills/ai-content-collaboration ~/.claude/skills/ - Confirm the
references/folder came along:ls ~/.claude/skills/ai-content-collaboration - Restart Claude Code and try a prompt like "design our AI-assisted content workflow and disclosure policy" to confirm the skill triggers.
View source on GitHub ↗License: MIT