Collaborate: A Claude Code Skill for Structured, Asynchronous Document Writing with Multi-Agent Handoffs
A developer built collaborate, a Claude Code skill that solves the coordination problem when multiple people write a document in separate Claude conversations. Instead of playing “wait, what did you decide on that section?” via Google Docs, the tool enforces a turn‑based workflow: each time a contributor picks up the document, Claude briefs them in plain English — what changed, what the previous person attempted, and what specific input is needed next. When the contributor finishes, the skill snapshots the document, logs the reasoning behind each change, and notifies the next person via Signal or Slack.
Key Features from the Source
- Turn handoff with reasoning capture: Claude produces a plain‑English summary of decisions, attempted approaches, and unresolved questions before passing the document to the next contributor.
- Parallel section ownership: Multiple writers can work on different sections simultaneously without stepping on each other’s changes.
- Structured critique & challenger/defender mode: Support for decision documents where one Claude instance argues for a position and another critiques it.
- Round robin review: Automatically cycles through contributors for sequential feedback.
- Storage: Document snapshots are stored on iCloud or Google Drive.
- Notification via Signal or Slack: Each handoff triggers a message to the next person.
Installation
Install the skill inside a Claude Code session by telling Claude:
install this skill: https://github.com/googlarz/collaborate/raw/main/SKILL.md
The full repository with documentation is at github.com/googlarz/collaborate.
Who It’s For
Teams already using Claude for writing who need structured, asynchronous collaboration — especially useful for policy docs, design specs, or any document where understanding the why behind changes matters as much as the final text.
📖 Read the full source: r/ClaudeAI
👀 See Also

ZSE: Open-source LLM inference engine with 3.9-second cold starts
ZSE is an open-source LLM inference engine that reduces 32B model memory requirements from 64GB to 19.3GB VRAM and achieves 3.9-second cold starts for 7B models using a pre-quantized .zse format with memory-mapped weights.

Driftwatch V3 Released: AI-Assisted Codebase Monitoring Tool
Driftwatch V3 is now available as a public repository after a 5-6 day build involving approximately 9,000 lines of code and $160 in API credits. The in-browser tool tracks markdown file issues, flags contradictory instructions, and provides cost tracking with recommendations.

Local Voice Control Setup for AI Agents on Apple Silicon
Setup local voice control for AI agents using Parakeet STT and Kokoro TTS on Apple Silicon for fast and cloud-independent interactions.

Fino: Open-Source MCP Server for Personal Finance Analysis with Claude
Fino is a free, open-source MCP server that connects Claude to bank accounts through Plaid, stores transaction data locally in SQLite, and provides Claude with tools for financial analysis.