Harbor — Development skill for Claude Code
Harbor is a framework for running agent evaluations and creating and using RL environments.
How to install Harbor
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open letta-ai/harbor and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Harbor does
Harbor is a framework for running agent evaluations and creating and using RL environments.
Alternatives in Development
- Oz Dev Environments — Predefined dev environments for running Oz Cloud Agents and integrations 48 ★
- Skill Evaluations Bottom 10 — Bottom 10 Skills: Skill-Judge Evaluations with TDD Improvements 26 ★
- Claude Code Root Runner — 🔥 Utility script to run Claude Code CLI with --dangerously-skip-permissions as root by creating temporary non 20 ★
README
Harbor
[](https://discord.gg/6xWPKhGDbA) [](https://harborframework.com/docs)
Harbor is a framework from the creators of [Terminal-Bench](https://www.tbench.ai) for evaluating and optimizing agents and language models. You can use Harbor to:
- Evaluate arbitrary agents like Claude Code, OpenHands, Codex CLI, and more.
- Build and share your own benchmarks and environments.
- Conduct experiments in thousands of environments in parallel through providers like Daytona and Modal.
- Generate rollouts for RL optimization.
Installation
uv tool install harbor
or
pip install harbor
Example: Running Terminal-Bench-2.0
Harbor is the offical harness for [Terminal-Bench-2.0](https://github.com/laude-institute/terminal-bench-2):
export ANTHROPIC_API_KEY=
harbor run --dataset terminal-bench@2.0 \
--agent claude-code \
--model anthropic/claude-opus-4-1 \
--n-concurrent 4
This will launch the benchmark locally using Docker. To run it on a cloud provider (like Daytona) pass the `--env` flag as below:
export ANTHROPIC_API_KEY=
export DAYTONA_API_KEY=
harbor run --dataset terminal-bench@2.0 \
--agent claude-code \
--model anthropic/claude-opus-4-1 \
--n-concurrent 100 \
--env daytona
To see all supported agents, and other options run:
harbor run --help
To explore all supported third pary benchmarks (like SWE-Bench and Aider Polyglot) run:
harbor datasets list
To evaluate an agent and model one of these datasets, you can use the following command:
harbor run -d "" -m "" -a ""
Citation
If you use **Harbor** in academic work, please cite it using the “Cite this repository” button on GitHub or the followin
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