MIT License

项目介绍

LearnPrompt/cc-harness-skills 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,采用 MIT License 许可证,目前获得 218 个 Star、63 次 Fork。

仓库全名
LearnPrompt/cc-harness-skills
开源许可证
MIT License
Star 数
218
Fork 数
63

README 摘要

CC Harness Skills Portable agent skills distilled from a publicly mirrored CC coding-agent codebase, then rewritten so they can be installed in Claude Code, Codex, and OpenClaw without depending on private runtime internals. This repo is not a source dump. It is a cleaned skill pack: prompts extracted into reusable templates host-agnostic helper scripts portable SKILL.md bundles release and smoke-test docs for…

完整内容见 GitHub 原始 README 或本页 。

常见问题

cc-harness-skills 用什么语言开发?

主要使用 Python 编写,采用 MIT License 许可证,目前有 218 个 Star。

cc-harness-skills 可以免费商用吗?

仓库采用 MIT License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 cc-harness-skills 的源码?

可以直接克隆仓库:git clone https://github.com/LearnPrompt/cc-harness-skills.git;安装与运行步骤见仓库 README。

cc-harness-skills 最近还在维护吗?

仓库最近一次更新为 6月13日,当前没有未关闭的 Issue;Star 数为 218,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

Portable CC-inspired skills for memory, verification, multi-agent coordination, context compression, and proactive coding-agent workflows.

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

语言占比

Python
Shell

贡献者

README

CC Harness Skills

Portable agent skills distilled from a publicly mirrored CC coding-agent codebase, then rewritten so they can be installed in Claude Code, Codex, and OpenClaw without depending on private runtime internals.

This repo is not a source dump. It is a cleaned skill pack:

  • prompts extracted into reusable templates
  • host-agnostic helper scripts
  • portable SKILL.md bundles
  • release and smoke-test docs for public distribution

If you are building with coding agents, these are the parts that usually separate a fun demo from a stable toolchain:

  • memory that stays useful instead of rotting
  • compression that preserves user corrections
  • verification that does not trust “done”
  • multi-agent routing that does not pollute the main context
  • proactive jobs with explicit limits

This repo packages those patterns into six installable skills.

Why This Exists

Most agent repos share the same hard problems:

  • how to keep memory useful without storing stale code facts
  • how to compress long conversations without losing user corrections
  • how to verify claimed completion instead of trusting it
  • how to coordinate multiple agents without turning the main context into garbage
  • how to add lightweight proactive behavior without building a dangerous daemon

The six skills in this repo package those patterns into download-ready bundles.

Who This Is For

  • builders who want better agent behavior without forking a full agent product
  • teams using Claude Code, Codex, or OpenClaw and wanting a shared skill layer
  • people studying CC-style harness design but needing something publishable and portable
  • anyone who wants prompts plus scripts, not prompts alone

Skill Pack

Public name Slug What it does Best hosts
CC Dream Memory dream-memory Consolidates logs, recent sessions, and topic memories into a short durable memory index. Claude Code, Codex, OpenClaw
CC Memory Extractor memory-extractor Extracts durable user, feedback, project, and reference memories from recent turns. Claude Code, Codex, OpenClaw
CC Verification Gate verification-gate Runs a read-only challenge pass after implementation to distinguish verified from merely claimed done. Claude Code, Codex
CC Swarm Coordinator swarm-coordinator Splits large work into research, synthesis, implementation, and verification with bounded workers. Claude Code, Codex, OpenClaw
CC Context Compressor structured-context-compressor Produces a nine-part continuation summary for long sessions and handoffs. Claude Code, Codex, OpenClaw
CC Kairos Lite kairos-lite Adds lightweight proactive jobs with schedule, sleep, brief, and expiry rules. Claude Code, OpenClaw

Each bundle lives in skills/ and includes:

  • SKILL.md
  • references/prompt-template.md
  • references/source-notes.md
  • scripts/...
  • README.md

Start Here

If you only try three things, try these first:

  1. install dream-memory
  2. install verification-gate
  3. install structured-context-compressor

That gives you one memory workflow, one quality gate, and one continuation artifact. It is the fastest way to feel whether this repo is useful.

Quick Start

Run the basic bundle checks first:

bash ./skills/check_all.sh

Install one skill into a host runtime:

mkdir -p ~/.claude/skills
cp -R ./skills/dream-memory ~/.claude/skills/

Then invoke it in Claude Code:

Use /dream-memory to consolidate the memory directory before we continue.
mkdir -p ~/.codex/skills
cp -R ./skills/dream-memory ~/.codex/skills/

Then invoke it in Codex:

Use /dream-memory and consolidate recent memory files into one stable index.
mkdir -p ~/.openclaw/workspace/skills
cp -R ./skills/dream-memory ~/.openclaw/workspace/skills/

Then check it in OpenClaw:

openclaw skills info dream-memory

Publish to ClawHub after checks:

bash ./skills/publish_all.sh 0.1.0

Release Docs

Naming

Recommended public GitHub repo name: cc-harness-skills

Good alternatives:

  • cc-agent-skills
  • cc-harness-kit
  • cc-portable-skills

The public naming uses CC on purpose: it signals the origin of the ideas without hard-coding a full vendor product name into the repo identity.

What Is Verified

Latest smoke-test status:

  • Claude Code: six skills load successfully
  • OpenClaw: six skills resolve as Ready
  • Codex: bundle structure is verified; runtime smoke test is pending local auth

Full report: skills/TEST_REPORT.md

Project Layout

skills/
  dream-memory/
  memory-extractor/
  verification-gate/
  swarm-coordinator/
  structured-context-compressor/
  kairos-lite/

Internal working notes and non-publishable local experiments still live under .codex/skills/, but the public release surface for this project is the root skills/ directory.

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