bundled-keep
Existing task skill that should remain after job-level skill injection.
- License 许可
- Apache-2.0
- 所属仓库
- PGCodeLLM/harbor
- 最近更新
- 2026-11-12
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- bundled-keep
- description
- Existing task skill that should remain after job-level skill injection.
02 资源文件 2
- 参考文档checklist.md4.3 KB
- 其他customize.toml1.6 KB
03 SKILL.md 正文
bundled-keep
This bundled task skill survived the runtime skill merge.
04 同仓库更多 Skills
upload-parity-experiments
Create or reuse Hugging Face dataset PRs for `harborframework/parity-experiments` and upload Harbor parity/oracle result folders efficiently with sparse checkout, raw git pushes, and Git LFS.
rewardkit
Write Harbor task verifiers using Reward Kit. Use when creating or editing a task's tests/ directory, adding grading criteria, setting up LLM/agent judges, or designing verifiers that produce a reward score.
publish
Publish a Harbor task or dataset to the registry. Use when the user wants to upload, publish, or share tasks or datasets/benchmarks on the Harbor registry.
create-task
Create a new Harbor task for evaluating agents. Use when the user wants to scaffold, build, or design a new task, benchmark problem, or eval. Guides through instruction writing, environment setup, verifier design (pytest vs Reward Kit vs custom), and solution scripting.
create-adapter
Scaffold a new Harbor benchmark adapter by running `harbor adapter init` and then guide implementation using the Adapters Agent Guide as the authoritative spec.
generate-greeting
Generate a greeting message and write it to a file.