By knowz-io
KnowzCode - Platform-agnostic AI development methodology with TDD, quality gates, and structured workflows
KnowzCode: Impact analysis and Change Set proposals
KnowzCode: Specification drafting, architecture review, and design decisions
KnowzCode: TDD implementation, verification loops, and code quality
KnowzCode: Finalization — specs, tracker, log, architecture, learning capture
KnowzCode: Persistent context and knowledge liaison — reads local context directly, dispatches vault readers in parallel, aggregates and pushes context, routes vault I/O across all phases
Run read-only quality audits on the existing codebase — spec completeness, architecture health, OWASP security scanning, integration consistency. Use when the user wants to AUDIT or SCAN existing code, not build new features.
Detect continuation intent and resume active WorkGroup workflow. Triggers when user says continue, keep going, resume, or similar continuation intent
Explore a topic, investigate the codebase, or produce a structured implementation plan using vault knowledge, impact analysis, architecture assessment, and project context. Use when the user wants to EXPLORE, RESEARCH, or PLAN before deciding whether to build.
Execute a targeted micro-fix for single-file changes under 50 lines. Use when asked to fix a small bug, typo, or localized issue. Redirects to /knowzcode:work for larger changes.
Initialize KnowzCode framework in the current project. Use when asked to set up, install, or bootstrap KnowzCode in a new or existing project.
Uses power tools
Uses Bash, Write, or Edit tools
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AI-Powered Knowledge & Development Tools
Your knowledge base, accessible to every AI tool you use. Structured development that actually ships quality code.
MCP Server · Knowz Plugin · KnowzCode Plugin · Install · Full Features
The Knowz MCP server is a universal connector between your knowledge base and the AI tools you already use. Built on the open Model Context Protocol standard, it works with any compatible AI — Claude, ChatGPT, Gemini, Copilot, Cursor, Windsurf, custom agents, or your own integrations.
One knowledge base. Every AI tool in your workflow.
Search, save, and query your knowledge base without leaving your editor. Knowz auto-detects when a conversation is relevant and surfaces the right context — or offers to capture new insights — without being asked.
/knowz ask "What's our convention for error handling?"
/knowz save "We chose Redis over Memcached for pub/sub support"
/knowz search "authentication patterns"
Turns chaotic AI coding into a disciplined loop: analyze impact, design specs, build with tests, audit quality, and ship. Approval gates at every step. Scales from quick fixes to complex multi-file features.
Works across 6 AI platforms — Claude Code, OpenAI Codex, Gemini CLI, GitHub Copilot, Cursor, and Windsurf.
/knowzcode:work "Build user authentication with email and password"
/knowzcode:explore "how is auth currently implemented?"
/knowzcode:fix "Fix typo in login button text"
# Add the marketplace
/plugin marketplace add knowz-io/knowz-skills
# Install plugins
/plugin install knowz@knowz-skills # Knowledge management
/plugin install knowzcode@knowz-skills # Structured development
# Get started
/knowz register # Create account + configure MCP
/knowzcode:init # Initialize in your project
/knowzcode:work "Build user authentication" # Start building
MIT License with Commons Clause — See individual plugin directories for details.
npx claudepluginhub knowz-io/knowz-skills --plugin knowzcodeFrictionless knowledge management via the Knowz MCP server — search, save, and query knowledge across vaults
Development workflow skills, commands, and hooks from claude-toolbox
Autonomous spec-driven development workflow with multi-agent collaboration, specification management, and task orchestration
AI-powered knowledge base management - Capture conversation learnings, maintain topic-specific KB files, Obsidian-compatible knowledge graph, structured dynamic context loading, and institutional knowledge in CLAUDE.md
Unified toolkit for Context-Driven Development with spec-first planning, TDD workflow, and Beads integration
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