Agent Native

harbor

Executes Harbor benchmarks using Ante as the agent, enabling benchmark runs and reproduction of Ante's published evaluation results.

by AntigmaLabsCommunity

Community author

Agents
Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode, claude.ai and API
License
Apache-2.0 (permissive)
Pin
fe0e3b2pinned Oct 9, 2026
Context cost
about 490 tokenswhen the skill loads
GitHub stars
2,003on antigmalabs/ante
Scripts
None found

What it does

“Run Terminal-Bench or any Harbor dataset with Ante as the agent, using the Harbor adapter in the ante repo's ante-harbor/ directory. Use when the user wants to benchmark Ante on Harbor or reproduce Ante's published eval results.”
The author's description, from SKILL.md

Generated summary from the skill's own text

Executes Harbor benchmarks using Ante as the agent, enabling benchmark runs and reproduction of Ante's published evaluation results. The skill configures and runs Harbor tasks in Docker containers, forwarding API credentials and installation parameters to the agent inside each sandbox.

When to use it

  • Benchmarking Ante against Harbor or Terminal-Bench datasets
  • Reproducing Ante's published evaluation results
  • Testing Ante performance across multiple tasks

When not to

  • Running Ante on single coding tasks without Harbor framework
  • When Docker is unavailable or sandboxing is not required

Install

These commands install from the publisher's repository and need no account.

skills CLI

npx skills add antigmalabs/ante --skill harbor

Installs from the repository's default branch, which may have changed since the commit we checked.

GitHub CLI 2.90 or later

gh skill install antigmalabs/ante harbor@fe0e3b2025d1dbd486637a5d09600d68b39a544d

Installs the commit we checked (fe0e3b2).

Copy by hand

Download the folder at fe0e3b2 and put it in .claude/skills/harbor for Claude Code and in .agents/skills/harbor for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.

Skill folder on GitHub at fe0e3b2

Copy for your agent

A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.

Prompt

Install the agent skill "harbor" by AntigmaLabs.

Source, pinned to commit fe0e3b2025d1dbd486637a5d09600d68b39a544d:
https://github.com/antigmalabs/ante/tree/fe0e3b2025d1dbd486637a5d09600d68b39a544d/curated/skills/harbor

1. Download that folder at exactly this commit. Do not use the default branch.
2. Copy every file unchanged, keeping the folder structure, into .claude/skills/harbor/ for Claude Code and .agents/skills/harbor/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist.
3. Do not edit the files, and do not run any script in the folder unless I ask you to.
4. When you are done, list the files you copied and where you put them.

Listing and checks: https://www.agentnative.dev/skills/antigmalabs/harbor

SKILL.md at the pin

---
name: harbor
description: >-
  Run Terminal-Bench or any Harbor dataset with Ante as the agent, using the
  Harbor adapter in the ante repo's ante-harbor/ directory. Use when the user
  wants to benchmark Ante on Harbor or reproduce Ante's published eval results.
metadata:
  argument-hint: "<provider> <model> [task ...]"
---

# Run Harbor with Ante

Run [Harbor](https://github.com/laude-institute/harbor) with Ante as the agent. The adapter (`ante_agent.py`) lives in the `ante-harbor/` directory of the [ante repo](https://github.com/AntigmaLabs/ante). Harbor imports it and installs Ante inside each task sandbox from the published install script.

## Prerequisites

- A checkout of [AntigmaLabs/ante](https://github.com/AntigmaLabs/ante), for `ante-harbor/`
- [uv](https://docs.astral.sh/uv/) with Python 3.12
- Docker running: Harbor executes each task in a container
- The provider API key exported in the shell

## Run

Resolve the model and provider from the user's request. From the repo's `ante-harbor/` directory (so `ante_agent:AnteAgent` is importable):

```bash
uv run --python 3.12 --with harbor harbor run \
  --agent ante_agent:AnteAgent \
  --model "<model_name>" \
  --ak provider=anthropic \
  --ak install_args= \
  --ae 'ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}' \
  --dataset terminal-bench/terminal-bench-2-1 \
  --n-attempts 1
```

Adjust for the request:

- `provider` selects which key Ante reads inside the sandbox. For `openai` or `gemini`, forward `OPENAI_API_KEY` or `GEMINI_API_KEY` with `--ae` instead.
- `install_args` picks the Ante build installed in each sandbox: empty for the latest release, or a version to pin.
- Scope: add `-i <task-id>` (repeatable) to run specific tasks. Smoke-test one task before a full run unless the user asks otherwise.
- Throughput: `--n-concurrent <n>` caps parallel sandboxes. `--n-attempts <n>` sets attempts per task; published leaderboard runs use 5.
- Custom endpoint: add `--ae 'MODEL_BASE_URL=${MODEL_BASE_URL}'` when routing through a proxy.

## Read results

Harbor prints a per-task summary and writes a run directory with per-trial output; each trial captures Ante's raw event log from `/logs/agent/ante.txt`. Task failures do not make `harbor` exit non-zero, so judge the run by the summary, not the exit code.

From antigmalabs/ante at fe0e3b2, shown as plain text under its license: Apache-2.0 (permissive). The license text is in LICENSE.

View SKILL.md on GitHub at fe0e3b2

Files

1 file, 2.3 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.

Skill folder on GitHub at fe0e3b2
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