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

agent-harness agent-memory ai-agent codex coding-agent
47
21
100% credibility
Found Apr 01, 2026 at 47 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A pack of portable skill bundles extracted and adapted from a coding agent codebase to enhance AI tools like Claude Code, Codex, and OpenClaw with better memory handling, verification, compression, coordination, and proactive features.

How It Works

1
🔍 Discover helpful AI skills

You hear about a collection of ready-made tools that make your AI coding assistant smarter at remembering things and checking work.

2
📖 Explore the skill pack

You look through the simple folders, each offering something useful like memory tidy-up or task checkers.

3
⭐ Pick your first skill

You choose one, like the dream memory tool, to keep track of important notes without clutter.

4
📂 Place it in your AI's folder

You copy the skill folder to the spot where your AI looks for extra abilities.

5
💬 Tell your AI to use it

In your chat with the AI, you say something like 'use dream-memory' and it springs into action.

6
✨ See the improvement

Your AI now organizes memories neatly, verifies work properly, and handles big tasks without forgetting details.

🎉 AI works like a pro

Your coding projects flow smoothly with reliable memory, checks, and coordination, saving you time and frustration.

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Star Growth

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AI-Generated Review

What is cc-harness-skills?

cc-harness-skills is a portable Python GitHub repo packing six CC-inspired skills for coding agents, tackling memory rot, unverified outputs, bloated contexts, and clunky multi-agent coordination. You get drop-in bundles with prompts, templates, and CLI helpers like memory consolidation scripts or task board generators that install via simple copy commands into Claude Code, Codex, or OpenClaw runtimes. It's a github portable app for agent workflows, solving the gap between demo toys and stable toolchains without vendor lock-in.

Why is it gaining traction?

These skills stand out as lightweight, host-agnostic fixes for agent pain points—proactive jobs with expiry rules, structured context compression that keeps user corrections, and verification gates that probe beyond "done" claims. Developers hook on the quick starts: run check_all.sh, copy to ~/.claude/skills, invoke with /dream-memory, and see durable memory indexes emerge. As a portable github cli companion or portable python github download, it ports CC patterns into any setup, beating full agent forks.

Who should use this?

Agent builders extending Claude Code or OpenClaw for repo patrols and bug hunts. Teams coordinating multi-agent swarms on large codebases without context pollution. CC harness students needing publishable, proactive coding-agent tools for memory extraction and verification in shared workflows.

Verdict

Grab it if you're prototyping agent skills—docs and smoke tests are solid for 47 stars, but the 1.0% credibility score flags early maturity; test in a sandbox first. Worth starring for portable github desktop integration potential.

(198 words)

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