claudeCode
context-engineering-kit/plugins/kaizen/skills/kaizen/SKILL.md at master · NeoLabHQ/context-engineering-kit
github.comGitHub - CloudAI-X/claude-workflow-v2: Universal Claude Code workflow plugin with agents, skills, hooks, and commands
/plugin marketplace add alirezarezvani/claude-skills
GitHub - alirezarezvani/claude-skills: A Collection of Skills for Claude Code and Claude AI for real-world Usage. Including Claude Code Subagents, Claude Code Commnads
- Terminal output
- Claude's input/output context
- Log files or traces
- Git commits or diffs
This skill wraps Varlock to enforce secure patterns and prevent accidental exposure.
GitHub - wrsmith108/varlock-claude-skill: Claude Code skill for secure environment variable management with Varlock. Never expose secrets in Claude sessions.
Automated Quality Gates? We use hooks to auto-format code, run tests when... See more
GitHub - ChrisWiles/claude-code-showcase: Comprehensive Claude Code project configuration example with hooks, skills, agents, commands, and GitHub Actions workflows
Just a moment...
VoiceMode MCP - Voice Mode for Claude Code
getvoicemode.comPAI getting even more capable every day.
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Given the few months of attempting to get this thing stable, I came up with what I believe is a much better solution to this.
Functionality Packages instead of a Mirror Platform.
Let me explain.
The whole point of PAI is for everyone to have their own system, including an open-source system like OpenCode or something homegrown. Having the system based on the Claude Code is an automatic deviation from that. One that I was okay with, but still wasn't pure.
Over the last week or two this became more of a wizard or a setup system that customizes PAI functionality that I release for your environment. So like running the setup script, and you put in your variables or whatever.
The natural progression for this, given the fact that we have this brilliant AI available to us now, is to have your own AI system evaluate what is released into the PAI project and have your system integrated into itself.
So what we are going to move to is a system I'm calling PAI Packages.
Tapestry weaves learning content into action. Extract any content (YouTube, articles, PDFs) and automatically create implementation plans.