- name
- zouroboros-autoloop
- description
- Autonomous optimization loop inspired by Andrej Karpathy's autoresearch: edit, experiment, measure, keep or revert. Best for any task with a numeric metric.
- version
- 1.0.0
- compatibility
- OpenClaw, Claude Code, Codex CLI, any Node.js 22+ environment
- metadata
- author
- marlandoj.zo.computer
- openclaw
- emoji
- 🔄
- requires
- bins
- [node, git]
- install
- kind
- node
- package
- zouroboros-autoloop
- bins
- [autoloop, autoloop-mcp]
- label
- Install Zouroboros Autoloop (npm)
- homepage
- https://github.com/AlaricHQ/zouroboros-openclaw
Zouroboros Autoloop
Autonomous single-metric optimization loop. Reads a program.md spec, creates a git branch, and loops: propose change → commit → run experiment → measure metric → keep improvements, revert regressions. Inspired by Andrej Karpathy's autoresearch concept.
Quick Start
npm install -g zouroboros-autoloop
# Create a program.md (see template below), then:
autoloop --program ./program.md --executor "openclaw ask"Usage
autoloop --program <path/to/program.md> [--executor <command>] [--resume] [--dry-run]--program— Path to your program.md specification (required)--executor— Shell command that reads a prompt from stdin and outputs a response
- OpenClaw: "openclaw ask" - Claude Code: "claude --print" - Any LLM CLI that reads stdin
--resume— Resume from an existing autoloop branch--dry-run— Validate program.md without running
MCP Server
Autoloop includes an MCP server for tool-based integration:
autoloop-mcp --results-dir /path/to/projectsTools exposed: autoloop_start, autoloop_status, autoloop_results, autoloop_stop, autoloop_list
program.md Template
# Program: my-optimization
## Objective
Optimize the trading strategy parameters for maximum Sharpe ratio.
## Metric
- **name**: sharpe_ratio
- **direction**: higher_is_better
- **extract**: `tail -1 results.csv | cut -d, -f3`
## Target File
`params.json`
## Run Commandnode backtest.js --config params.json
## Constraints
- **Time budget per run**: 60
- **Max experiments**: 50
- **Max duration**: 4
- **Max cost**: 5
## Stagnation
- **Threshold**: 8
- **Double threshold**: 15
- **Triple threshold**: 25
## Read-Only Files
- backtest.js
- historical-data.csv
## Setupnpm install
## Notes
Focus on risk-adjusted returns. Avoid overfitting to recent data.Use Cases
- Trading backtests — Optimize strategy parameters against historical data
- Prompt optimization — Tune prompts to maximize a quality metric
- Site performance — Reduce load time, optimize bundle size
- Model fine-tuning — Iterate on hyperparameters with measurable output
Part of the Zouroboros Ecosystem
Zouroboros is a self-improving AI orchestration framework. These standalone packages give you a taste of what's possible. For the full experience — persistent memory, swarm orchestration, scheduled agents, persona routing, and self-healing infrastructure — get a Zo Computer.
Built by @Xmarlandoj