/examples folder contains production-quality working code for every major use case — copy these before writing your own implementation from scratch.The OpenClaw GitHub repository is your best resource after the official documentation — but only if you know where to look. We've seen engineers spend a week building something that already exists in the examples folder because they didn't know it was there. Here's the full map.
Repository Structure Map
The OpenClaw repository is organized into clearly separated areas, each serving a distinct purpose. Understanding this structure saves hours of aimless browsing.
| Directory | Contents | How Often to Visit |
|---|---|---|
| /src | Core framework source code | When debugging deep issues |
| /examples | Working code for all major patterns | Before building anything new |
| /docs | Reference documentation source | For contributing doc improvements |
| /tests | Test suite — reveals expected behavior | When official docs are unclear |
| /plugins/scaffold | Template for building new plugins | Starting point for custom plugins |
The /examples directory is the most underused resource in the entire ecosystem. We'll get to the exact examples worth copying in a moment — but first, understand why the tests directory is secretly one of the most useful places in the repo.
Tests reveal the contract between OpenClaw's internals and its public API. When documentation says something "should work" but doesn't quite explain how, finding the relevant test shows you the exact inputs and expected outputs the maintainers designed for. This is especially valuable for edge cases like agent failure handling, tool timeout behavior, and provider fallback logic.
examples/README.md in the repo provides a categorized index of every example with a one-line description. This is the fastest navigation aid in the repository. Read it before exploring any subdirectory.The Examples Worth Copying
As of OpenClaw v1.8 in early 2025, the examples directory contains over 40 working code samples. Most are useful. A handful are essential. Here are the ones we use as starting points most often:
single-agent-with-tools
This is the canonical starting point for any new project. It shows a properly structured agent with tool definitions, error handling, and result extraction. The code pattern here is worth memorizing — it's the baseline that everything else builds on.
multi-agent-sequential
A pipeline where Agent A produces output, passes it to Agent B, which passes it to Agent C. Sequential patterns are the most common multi-agent use case. This example shows the cleanest way to implement handoffs with proper result typing and failure escalation.
provider-fallback
This one is critical for production deployments. It shows how to configure OpenClaw to fall back to a secondary provider if the primary provider is unavailable or rate-limited. The pattern here prevents the #1 cause of production agent failures: single-provider dependency.
memory-persistent
Shows how to wire up persistent memory using a vector store backend. Essential for any agent that needs to remember information across sessions. The example uses a local ChromaDB instance for development — the same code works with production vector databases by changing the connection config.
# Quickly clone and run any example:
git clone https://github.com/openclaw/openclaw.git
cd openclaw/examples/single-agent-with-tools
pip install -r requirements.txt
export ANTHROPIC_API_KEY="your-key"
python main.pyUsing GitHub Issues as a Learning Resource
The Issues tab is a goldmine that almost nobody mines.
When you hit a problem with OpenClaw, the answer is almost always in a closed issue. The community has been active long enough that most common problems — provider connection errors, tool timeout handling, memory configuration edge cases, multi-agent deadlock patterns — have been reported, discussed, and resolved in public.
The most useful filter combinations:
- label:question + is:closed — Real usage questions with real answers from maintainers
- label:bug + is:closed + milestone:v1.8 — Bugs that were fixed in your version, showing what changed and why
- label:good-first-issue + is:open — Good for understanding how the codebase is organized if you want to contribute
One specific pattern that has saved us hours: searching for the exact error message you're seeing as a GitHub Issues search query. Error messages in OpenClaw are usually unique enough that this surfaces the exact thread where the same problem was already diagnosed.
Community Forks and Extensions
Several community forks of OpenClaw have built real production value on top of the core. These aren't alternatives to OpenClaw — they're extensions that add capabilities the core team hasn't prioritized yet.
The most notable extensions as of early 2025 that are worth evaluating:
Production monitoring overlays. Community-built middleware that wraps OpenClaw's agent execution with detailed telemetry: token usage per agent, latency per tool call, error rates, and cost tracking. If you're deploying at scale and need visibility, this category of extension is worth the evaluation time.
Advanced memory backends. Forks that add direct integration with enterprise vector databases beyond what core OpenClaw ships with. If your use case requires very large memory stores or specific database integrations already in your infrastructure, check the community repos before building custom integrations.
Provider-specific optimizations. Some community members who work heavily with specific AI providers have published configurations and routing logic that improves performance and reduces costs for specific provider + use case combinations. These are often found as GitHub Gists rather than full forks.
The best place to find these is the community Discord's #resources channel — the links there are more current than any static list we could maintain here.
Common Mistakes When Using the Repo
Building on main instead of a release tag is the single most common mistake. Main branch code is in active development. Breaking changes can appear between any two commits. For any production or serious development work, always pin to a specific release tag.
Not running the test suite after cloning. Before building anything on top of the repo, verify that the tests pass in your environment. Occasional CI-only configurations mean tests that pass on GitHub Actions don't always pass locally — surfacing this early avoids blaming OpenClaw for problems that are actually environment issues.
Ignoring the CHANGELOG.md. Every release documents what changed, what was deprecated, and what was fixed. Reading the changelog between your current version and the latest release takes five minutes and prevents 80% of upgrade problems before they happen.
Contributing without reading CONTRIBUTING.md first. The maintainers have strong preferences about code style, test coverage, and the issue-before-PR workflow. Contributing without reading this results in PRs that are rejected for process reasons rather than code quality, which wastes everyone's time.
Frequently Asked Questions
Where is the official OpenClaw GitHub repository?
The official OpenClaw repository is maintained by the core team and contains the main source, official examples, and the contributing guide. The README always links to the latest stable release, current documentation site, and the community Discord. Verify you're on the official org's account, not a fork, before following setup instructions.
What is in the OpenClaw GitHub examples folder?
The examples folder contains over 40 working code samples for common patterns: single-agent setups, multi-agent workflows, provider configurations, tool integrations, and deployment templates. Each example is self-contained and designed to run with minimal modification — the fastest way to understand real usage patterns.
How do I contribute to OpenClaw on GitHub?
Read CONTRIBUTING.md in the repository root before submitting anything. Contributors must sign the CLA, follow documented coding standards, and open an issue before significant work begins. Small bug fixes can be submitted directly as pull requests without prior issue discussion.
Are there official OpenClaw starter templates on GitHub?
Yes. The official repository includes starter templates for local development, Docker deployment, and cloud provider setups. Community members have extended these with production logging, monitoring, and secrets management. Search the GitHub topics "openclaw-template" to find community-maintained starters.
How often is the OpenClaw GitHub repo updated?
The main branch receives commits multiple times per week. The stable release branch updates less frequently, following a release cycle that prioritizes stability. Watch the Releases page rather than the main branch for production-ready updates to avoid picking up unstable code.
What GitHub Issues are most useful for learning OpenClaw?
Closed issues labeled "question" and "good first issue" contain the best real-world usage patterns and troubleshooting. Searching your exact error message in Issues is particularly effective — OpenClaw error messages are specific enough to reliably surface the thread where your problem was already resolved.
Can I build private plugins without publishing to GitHub?
Yes. The plugin system works entirely with local plugins that never need to be published. Develop, test, and deploy custom plugins within your private infrastructure. Publishing to ClaWHub is optional and only necessary if you want to share plugins with the broader community.
What is the best branch to build on from the OpenClaw GitHub repo?
Always build on the latest stable release tag, not the main branch. Main may contain experimental features or undocumented breaking changes. As of early 2025, tag v1.8 is the recommended stable baseline for all new projects and production deployments.
M. Kim has evaluated and onboarded teams onto dozens of open-source infrastructure projects, with a focus on AI agent frameworks since 2023. He contributed to the OpenClaw examples directory and maintains several community resources that help new builders navigate the ecosystem efficiently.