idea-storm

What This Skill Does

Idea Storm is an advanced, automated laboratory for engineering and scientific experimentation within OpenClaw. It manages the entire lifecycle of an idea—from initial research and architectural design to implementation, automated verification, and iterative optimization. By employing a unique multi-stage 'spawn' architecture, Idea Storm executes complex tasks in isolated sub-agent environments, ensuring your main chat session remains fluid and unblocked. It maintains rigorous state persistence via experiment.yaml files and synchronizes finalized results to Notion for long-term knowledge retention.

Installation

To integrate Idea Storm into your environment, run the following command in your OpenClaw terminal: clawhub install openclaw/skills/skills/c4chuan/idea-storm

Use Cases

• Algorithm Development: Rapidly prototyping and testing new machine learning models or heuristic improvements.
• System Optimization: Automating the benchmarking of code performance against specific latency or resource constraints.
• Complex Engineering Research: Systematically exploring various technical approaches for a new feature, comparing tradeoffs, and documenting the winning solution.
• Automated QA: Running iterative verification tests on code changes to ensure they meet performance thresholds (e.g., FID score, latency, or function coverage).

Example Prompts

1. "Idea-storm: I need to build a RAG system for internal documents. Can you research potential architectures and propose the most efficient design?"
2. "Experiment一下：我现在的 Python 脚本跑得太慢了，帮我尝试不同的并发方案并验证性能提升效果。"
3. "迭代优化：上轮设计的分布式缓存方案表现不错，但需要进一步提升写入并发数，请尝试新的锁机制并重新验证。"

Tips & Limitations

• Context Persistence: Always check the experiment.yaml file within the experiments/ directory to understand the current progress and recovery state of your experiments.
• Notion Integration: Ensure your OpenClaw Notion credentials are set up correctly to enable the long-term documentation features of this skill.
• Monitoring: While the agent runs in the background, you will receive 'announce' messages in your main session when specific check-points are reached.
• Limitations: This skill is best suited for modular, testable engineering tasks. It relies on clearly defined validation.mode settings to distinguish between successful and unsuccessful iterations. Highly creative tasks that lack objective success metrics may require more frequent human intervention.