By naimkatiman
The 7 Laws of AI Agent Discipline with Claude Code and Codex-ready skills, hooks, commands, instinct packs, and MCP tools.
Reflect on the current session, analyze observations for patterns, and show instinct status. Runs on-demand to save tokens.
Visual dashboard showing instinct health, observation stats, and learning progress
Quick reference card for the 7 Laws of AI Agent Discipline
Create and maintain task_plan.md, findings.md, and progress.md for persistent file-based planning
Convert PRD to executable JSON and run autonomous agent loop until all stories complete
Install structured self-improvement loops with instinct-based learning into Claude Code — research, plan, execute, verify, reflect, learn, iterate. On-demand or weekly analysis to save tokens. Supports multi-agent parallel analysis.
Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete. Converts PRDs to executable JSON, implements stories iteratively with quality checks, and tracks progress.
Agentic skills framework with mandatory workflows. Activates skills automatically before tasks: brainstorming, git-worktrees, writing-plans, test-driven-development, code-review, and more.
Audit the active repo, MCP servers, plugins, connectors, env surfaces, and harness setup, then recommend the highest-value ECC-native skills, hooks, agents, and operator workflows. Use when the user wants help setting up Claude Code or understanding what capabilities are actually available in their environment.
Matches all tools
Hooks run on every tool call, not just specific ones
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Stop your AI agent from skipping steps, guessing, and declaring "done" without verifying.
New here? → QUICKSTART.md gets you working in 2 minutes.
AI agents are great at individual steps. They're terrible at discipline.
They skip research. They plan loosely. They declare "done" before verifying. They add features mid-task. They never reflect. Each session, they repeat the same mistakes.
The 7 Laws fix that — plus a learning system (Mulahazah) that builds instincts over time. No config, no daemon, no manual setup.
You: Add rate limiting to the /api/users endpoint
Agent: I'll add rate limiting now.
*writes express-rate-limit middleware*
Done! I've added rate limiting to the /api/users endpoint.
You: Did you check if we already have rate limiting somewhere?
Agent: Let me check... oh, there's already a rate limiter in middleware/rateLimit.ts.
I've created a duplicate. Let me fix that.
You: Did you test it?
Agent: Let me run the tests... they're failing. The import path is wrong.
*fixes import*
Now it works!
You: You also broke the /api/auth endpoint — it was sharing that middleware.
Agent: I see. Let me fix that too...
Result: 4 back-and-forth corrections. Duplicate code. Broken endpoint. 15 minutes wasted.
You: Add rate limiting to the /api/users endpoint
Agent: **[Law 1: Research]** Searching for existing rate limiting...
Found: middleware/rateLimit.ts — already applies to /api/auth.
Found: express-rate-limit already in package.json.
**[Law 2: Plan]**
WILL: Extend existing rateLimit middleware to cover /api/users
WILL NOT: Create new middleware or change existing /api/auth behavior
VERIFY: Run tests + curl /api/users 101 times to confirm 429 response
**[Law 3: Execute one thing]** Adding /api/users to the route list
in middleware/rateLimit.ts...
**[Law 4: Verify]**
✓ npm test — 47/47 passing
✓ curl test — 429 after 100 requests
✓ /api/auth still works — 200 OK
npx claudepluginhub naimkatiman/continuous-improvement --plugin continuous-improvementHarness-native ECC plugin for engineering teams - 67 agents, 271 skills, 92 legacy command shims, reusable hooks, rules, MCP conventions, and operator workflows for Claude Code plus adjacent agent harnesses
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.