A highly structured, three-stage workflow for collaboratively drafting, refining, and testing professional documentation with an AI agent.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install coauthoring
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install coauthoring using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Doc Co-authoring?
The Doc Co-authoring skill transforms the way technical documentation and proposals are created by using a guided, multi-stage process. Instead of simple prompting, this Openclaw Skills integration acts as an active guide, moving users through deliberate phases of context gathering, iterative drafting, and rigorous reader testing to ensure the final output is high-impact and clear.
By focusing on closing the context gap between the user and the AI, this skill minimizes generic filler and produces documents that work effectively even when read by others without prior knowledge. It is specifically designed for high-stakes writing tasks where clarity and technical accuracy are paramount.
Doc Co-authoring Use Cases
- Drafting technical specifications, PRDs, or RFCs with deep architectural context.
- Creating decision docs that require capturing complex trade-offs and team discussions.
- Authoring project proposals where the primary audience and desired impact are specific and high-stakes.
- Refining existing documentation by generating alt-text for images and checking for logical contradictions.
How Doc Co-authoring Works
- Context Gathering: The agent asks targeted questions about audience, goals, and constraints while the user provides raw info-dumps or connects external data sources.
- Structure Agreement: A scaffold is created based on templates or suggested sections, establishing a roadmap for the document.
- Iterative Refinement: Sections are built one by one through a process of brainstorming 5-20 options, curation, and surgical editing.
- Reader Testing: A fresh AI instance with no prior context tests the document to identify blind spots and verify that it answers critical reader questions.
- Final Review: A quality check for flow and consistency is performed before the document is finalized for the intended audience.
Doc Co-authoring Setup
To enable this workflow within your environment, ensure your agent has access to the necessary workspace integrations. Use the following commands to check or initialize your environment:
# List available skills to ensure doc-coauthoring is active
openclaw skills list
# Enable connectors for Google Drive or Slack to enhance context gathering
openclaw connectors enable google_drive
openclaw connectors enable slack
Doc Co-authoring Data Schema & Taxonomy
The skill manages documentation through a structured lifecycle of files and metadata:
| Feature | Description |
|---|---|
| Work-in-Progress | Uses create_file for initial scaffolds and str_replace for surgical updates. |
| Meta-Context | Tracks audience profiles, desired impact, and template constraints. |
| Artifacts | Generates Markdown files (e.g., technical-spec.md) in the working directory. |
| Testing Logs | Captures output from sub-agents during the Reader Testing phase to log ambiguities. |
Doc Co-authoring Advanced Features
- Sub-agent Validation: Automatically invokes fresh AI instances to simulate a 'cold' reader and catch internal contradictions.
- Surgical Edits: Utilizes precise string replacement to update documents without reprinting the entire text, preserving focus and context.
- Multi-channel Contextualization: Integrates with Slack, Teams, and SharePoint via MCP servers to pull in real-time team discussions.
- Automated Alt-text Generation: Scans documents for images and generates descriptive alt-text to improve accessibility and AI discoverability.
SKILL.md
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