cc-harness-skills

Name: cc-harness-skills
Author: LearnPrompt

Verified

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

219stars

63forks

Python

Installation

# Add to your Claude Code skills
git clone https://github.com/LearnPrompt/cc-harness-skills

Getting Started

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Security ReportVerified

Last scanned: 5/30/2026

{
  "issues": [],
  "status": "PASSED",
  "scannedAt": "2026-05-30T15:33:32.671Z",
  "npmAuditRan": true,
  "pipAuditRan": true
}

README.md

Frequently Asked Questions

What is cc-harness-skills?

cc-harness-skills is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by LearnPrompt. Portable CC-inspired skills for memory, verification, multi-agent coordination, context compression, and proactive coding-agent workflows. It has 219 GitHub stars.

Is cc-harness-skills safe to use?

Yes. cc-harness-skills passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install cc-harness-skills?

Clone the repository with "git clone https://github.com/LearnPrompt/cc-harness-skills" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is cc-harness-skills written in?

cc-harness-skills is primarily written in Python. It is open-source under LearnPrompt on GitHub, so you can review or fork the full source.

Are there alternatives to cc-harness-skills?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh cc-harness-skills against similar tools.

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Related Skills

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An agentic skills framework & software development methodology that works.

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CC Harness Skills

"The parts that separate a fun demo from a stable toolchain: memory, compression, verification, routing, proactive jobs."

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:

install dream-memory
install verification-gate
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

One-line install (any skills-compatible agent):

# all six skills
npx skills add LearnPrompt/cc-harness-skills -g

# or a single skill
npx skills add LearnPrompt/cc-harness-skills -s verification-gate -g

Or copy one skill into a host runtime manually:

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

Publisher guide: skills/README.md
Release order and copy: skills/RELEASE_PLAN.md
Smoke-test report: skills/TEST_REPORT.md

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.

Made by LearnPrompt · From the same workshop

Luban · skill polishing · Paoding · blogger distilling · Cailun · chat-to-page · Afu · LLM todo · AI News Radar · zero-API · Skillrush Town · ClawHub daily · Irasutoya Illustrations · Humanize PPT · CC Harness

WeChat「卡尔的AI沃茨」 · X @aiwarts · learnprompt.pro