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Works with the AI Agents you already use
handOff.
Save and resume agent tasks across sessions and tools using structured handoff files and automated log recovery.
$10
handOff.
Example session with this skill installed
My tokens are almost gone and I need to switch to Cursor. Save my progress on the user authentication refactor so the next agent knows where I stopped and what to do next.
- Read your context and instructions
- Compiled the handoff
I have captured the current state of the authentication refactor and updated HANDOFF.md at the project root. I also ran the log parser to include the last five terminal commands and the specific trace from the failing unit test.
HANDOFF: User authentication refactor
Updated: 2024-10-24 14:30 UTC | By: claude-3-5-sonnet | Status: In progress
Next agent: read this whole file, check it against the repo (git status), then continue from "Next steps". Keep this file updated as you work.
Goal
Refactor the AuthService to support JWT rotation and move sensitive logic from AuthController to the service layer. Done means all tests in tests/auth.spec.ts pass and the .env.example is updated.
Where we stopped
Mid-refactor of src/services/auth.service.ts. I just extracted the generateRefreshToken method, but src/controllers/auth.controller.ts is currently broken because it still expects the old method signature. The last test run failed with a TypeError at line 42.
Next steps
- Update
AuthController.loginto use the newAuthService.createSessionsignature. - Fix the broken import in
src/middleware/session.ts. - Run
npm test tests/auth.spec.tsto verify the fix.
Done so far
- Created
src/types/auth.d.tsfor standardized token shapes. - Moved
signTokenlogic from controller to service.
Tried and failed / gotchas
- Attempted to use
crypto.randomUUID()for tokens, but the environment requiresuuidv4 for compatibility with the existing Redis schema.
Key files
src/services/auth.service.ts- Core logic being refactored.src/controllers/auth.controller.ts- Currently in a broken state.
Next steps
- Open this project in Cursor.
- Run
git statusto confirm the uncommitted changes in the service layer. - Type "Read HANDOFF.md and continue" to resume.
Connects securely to your tools. The creator never sees your data.
About this skill
Stop losing progress when context windows fill up or usage limits hit without warning. When a session ends abruptly, the next agent starts from zero, wasting time and tokens re-learning the task. HANDOFF solves this by maintaining a HANDOFF.md file at the project root that captures the goal, the plan, failed attempts, and the exact state of half-finished work. It ensures continuity across different tools, models, and sessions.
What it does
- State preservation captures goals, specific code locations, and the current hypothesis in a format readable by any LLM.
- Log recovery extracts data from session logs of major coding CLIs (Claude Code, Cursor, Aider, etc.) to rebuild state after a crash.
- Automated context tracking runs a Python script to pull recent commands, changed files, and error messages directly into the handoff file.
- Cross-tool compatibility allows you to switch from Claude to Gemini or Cursor while keeping the agent focused on the next immediate step.
- Session protection monitors active sessions to warn about impending limits and ensures a checkpoint exists before the context window expires.
How it works
- Initialize by asking the agent to "write a handoff" or "save progress" when tokens are low or a milestone is reached.
- Execute script using
python3 scripts/handoff.py now --tool AGENTto automatically populate repo facts and session history. - Resume work in a new session by instructing the agent to "read HANDOFF.md and continue."
- Recover logs by running the
sessionscommand to find and digest the history of a session that ended due to a timeout or limit.
Frameworks & tools
The core logic resides in a standalone Python 3.8+ script using only the standard library and git. It supports session log parsing for Claude Code, Codex, Cursor, Gemini CLI, Copilot CLI, OpenCode, Qwen Code, Codebuff, and Aider.
Why this beats prompting it yourself
Manual prompting often forgets the "why" behind decisions or fails to list the specific files that are currently broken. This skill enforces a structured template and uses a script to pull objective data (like exact error messages and git status) that a human or LLM might misremember when context is tight.
Use cases
- Migrating a complex task from one AI tool to another due to rate limits.
- Resuming a long-running refactor after a weekend or session timeout.
- Recovering context after a CLI tool crashes or the API returns a credit error.
- Checking in progress during multi-step features to prevent hallucinations as context fills.
Known limitations
Requires Python 3.8+ for log parsing and automated repo tracking. Background session protection requires a local installation to run the watcher process.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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