This page collects concrete ways to use OpenHarness without overselling the project. Each example is intended to be small, reproducible, and easy to extend.
Use OpenHarness as a lightweight local coding agent for reading code, making edits, and running validation commands.
uv run ohExample prompt:
Review this repo, identify the highest-risk bug, patch it, and run the relevant tests.
The print mode is useful when you want structured output in shell pipelines or automation jobs.
uv run oh -p "Summarize the purpose of this repository" --output-format json
uv run oh -p "List files that define the permission system" --output-format stream-jsonOpenHarness can load Markdown skills and Claude-style plugin layouts, which makes it useful for experimentation with custom workflows.
Examples:
- Put a custom skill in
~/.openharness/skills/. - Install a plugin into
~/.openharness/plugins/. - Use the same workflow conventions across multiple local projects.
The repo includes team coordination primitives, background task management, and task inspection tools.
Example prompts:
Spawn a worker to audit the test suite while you inspect the CLI command registry.
Create a background task that runs the slow integration script and report back when it finishes.
OpenHarness is useful when you need to compare Anthropic-compatible backends behind one harness.
Typical scenarios:
- Default Anthropic setup.
- Moonshot/Kimi through an Anthropic-compatible endpoint.
- Vertex-compatible and Bedrock-compatible gateways.
- Internal proxies that expose an Anthropic-style API surface.
See the provider compatibility table in README.md.
If you are evaluating the project rather than contributing code, start here:
README.mdfor install, usage, and architecture.CONTRIBUTING.mdfor contributor workflow.CHANGELOG.mdfor visible repo changes.
Good showcase additions are:
- Based on a real workflow you ran.
- Short enough to reproduce locally.
- Honest about prerequisites and limitations.
- Focused on what OpenHarness makes easier, not on generic LLM claims.