Basic Information
| Item | Details |
|---|
| Product Name | OpenClaw Cookbook / Best Practices |
| Product Type | Best Practices and Usage Guides |
| Source | Community Practices, Official Documentation, Technical Blogs |
| Relation to OpenClaw | Experience Accumulation and Knowledge Base |
Product Overview
The OpenClaw Cookbook is a collection of best practices accumulated by the community, covering various aspects from architectural design to daily operations. These practices are derived from over 200 hours of in-depth usage experience, contributions from 800+ developers, and countless iterations and optimizations.
Core Best Practices
1. Agent Design Principles
- Single Responsibility - If you can't describe an agent's function in one sentence, it's doing too much
- Timely Splitting - When an agent's logic exceeds 5 conditional branches, it should be split into two agents
- Low Overhead - Adding an agent in OpenClaw has low overhead, while debugging a bloated agent is costly
2. Performance Optimization
| Practice | Effect |
|---|
| Parallel Sub-agent Calls | Reduces 45-second serial tasks to under 20 seconds |
| Cache Repeated Queries | Reduces model call costs by 30-50% |
| Model Warm-up | Avoids first-request latency spikes |
| Precompile Prompt Templates | Reduces repetitive computation |
3. Model Switching Strategies
- Perform short-context warm-up runs after model switching
- Precompile prompt templates and reload key memory channels
- OpenClaw's rolling strategy supports model warm-up
- Choose appropriate models for different tasks
4. Cost Control
- Cache common queries to reduce API calls
- Use local LLMs (Ollama) to lower costs
- Set context window size appropriately
- Avoid unnecessary full-text searches
Workflow Design Best Practices
Parallel Processing
Scenario: Need to research three independent topics before synthesizing a response
Serial Approach: 45 seconds
Parallel Approach: <20 seconds
Improvement: Launch three concurrent sub-agent calls
Task Layering
| Layer | Description | Example |
|---|
| Exploration Layer | Low-risk, exploratory tasks | Information search, document reading |
| Execution Layer | Medium-risk, reversible operations | Email drafts, calendar creation |
| Controlled Layer | High-risk, approval-required operations | Database writes, infrastructure changes |
Real-world Use Cases
- Weekly Meal Planning - 2026 annual meal plan template, shopping list sorted by store and aisle, automatic weather forecast updates
- GitHub Issue Auto-classification - Automatic labeling, priority assignment, expiration cleanup
- Content Creation Automation - YouTube content generation and publishing workflow
200+ Hours of Usage Experience Summary
14 Advanced Tips (MindStudio Summary)
- Keep agent responsibilities single
- Leverage parallel processing for speed
- Cache appropriately to reduce costs
- Warm up models after switching
- Set appropriate security boundaries
- Regularly back up memory data
- Monitor agent behavior and performance
- Use templates to standardize workflows
- Gradually increase automation scope
- Keep humans in the loop
- Test exception handling
- Document custom configurations
- Stay updated with community updates and security patches
- Regularly audit agent permissions
Sources
External References
Learn more from these authoritative sources: