A professional framework for creating detailed handoff documents that allow fresh AI agents to resume complex work with zero context loss.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install session-handoff
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install session-handoff using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Session Handoff is a critical utility designed to solve the persistent problem of context window exhaustion in long-running AI development sessions. By generating structured, validated handoff documents, this skill ensures that any fresh agent can pick up exactly where a previous one left off, maintaining full awareness of technical decisions, current state, and immediate priorities. It is an essential part of the Openclaw Skills library for managing large-scale engineering projects.
This skill provides a formalized protocol for both saving and resuming work. Whether you are reaching a token limit, switching between models, or pausing work for the day, Session Handoff captures the nuanced rationale and environmental state that would otherwise be lost. By integrating this into your workflow, you leverage the full power of Openclaw Skills to maintain continuity across fragmented chat sessions.
To implement Session Handoff within your Openclaw Skills environment, utilize the provided Python utility scripts located in your project's script directory.
# Generate a new handoff scaffold for a specific task
python scripts/create_handoff.py [task-slug]
# Validate the handoff for quality and security before closing the session
python scripts/validate_handoff.py .claude/handoffs/YYYY-MM-DD-slug.md
# List and check the status of existing handoffs
python scripts/list_handoffs.py
Session Handoff stores data in a structured directory at .claude/handoffs/ using a timestamped naming convention. This ensures a clean history of progress within the Openclaw Skills ecosystem.
| Data Component | Purpose |
|---|---|
| Metadata | Tracks timestamps, project paths, and git branch state. |
| State Summary | A high-level overview of what has been accomplished. |
| Critical Context | Information the next agent must know to avoid errors. |
| Decision Log | Captures the 'why' behind specific code or architecture choices. |
| Next Steps | A prioritized, actionable list for immediate continuation. |
| Quality Score | A numeric metric (0-100) generated during validation. |
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