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Peninsula School District's comprehensive Claude Code plugin system with proven workflow automation and experimental self-improving meta-learning

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PSD Claude Coding System

Peninsula School District's comprehensive Claude Code plugin system for AI-assisted software development.

License: MIT Claude Code Status

Overview

One unified plugin combining battle-tested development workflows with self-improving meta-learning.

Version: 1.12.1 Status: ✅ Production-Ready Workflows + 🧪 Experimental Meta-Learning

Quick Start

# Install the marketplace
/plugin marketplace add psd401/psd-claude-coding-system

# Install the unified plugin (one command!)
/plugin install psd-claude-coding-system

# Start using immediately
/work 347              # Implement an issue
/test                  # Run tests
/meta_health           # Check system status (after 2-4 weeks)

What's Inside

Workflow Commands (18 total)

Development Workflows (9 commands):

  • /work - Implement solutions + automatic security review on PR creation
  • /architect - System architecture via architect-specialist agent
  • /test - Comprehensive testing with coverage validation
  • /review_pr - Handle PR feedback systematically
  • /security_audit - Manual security audit wrapper (auto-runs in /work)
  • /issue - AI-validated GitHub issues with latest docs + optional architecture
  • /product-manager - Product specs → validated epic + auto-created sub-issues
  • /compound_concepts - Find automation opportunities (manual)
  • /clean_branch - Post-merge cleanup + automatic compound learning extraction

Meta-Learning Commands (9 commands):

  • /meta_health - Check system status & metrics
  • /meta_analyze - Find patterns in your workflow
  • /meta_learn - Get improvement suggestions
  • /meta_implement - Apply improvements safely (with dry-run)
  • /meta_improve - Full weekly improvement pipeline
  • /meta_document - Auto-update documentation from code
  • /meta_predict - Forecast future issues
  • /meta_experiment - A/B test ideas safely
  • /meta_evolve - Improve AI agents via genetic algorithms

AI Agents (17 total)

Workflow Specialists (12 agents):

  • NEW: architect-specialist, security-analyst-specialist
  • Existing: backend-specialist, frontend-specialist, test-specialist, performance-optimizer, database-specialist, documentation-writer, llm-specialist, plan-validator, gpt-5

Meta-Learning Specialists (5 agents): meta-orchestrator, code-cleanup-specialist, pr-review-responder, document-validator, breaking-change-validator

Latest Models: All agents use claude-sonnet-4-5 and claude-opus-4-1 (Oct 2025) with extended-thinking enabled

Read full documentation →

Documentation

For detailed planning docs, see:

  • Desktop: ~/Desktop/PSD-Meta-Learning-System-Plan.md (Full 6-phase plan)
  • Desktop: ~/Desktop/PSD-Plugin-Migration-Guide.md (Installation guide)

Installation

From GitHub (Recommended)

/plugin marketplace add psd401/psd-claude-coding-system
/plugin install psd-claude-coding-system

From Local Directory

/plugin marketplace add ~/non-ic-code/psd-claude-coding-system
/plugin install psd-claude-coding-system

Usage Examples

Basic Workflow

# Work on an issue
/work 347

# Run tests
/test

# Review PR
/review_pr 123

# Clean up after merge
/clean_branch

Meta-Learning (Experimental)

# Let it observe for a week, then:
/meta_analyze

# See improvement suggestions
/meta_learn

# Check system health
/meta_health

Features

Workflow Automation

  • ✅ 9 battle-tested development commands
  • ✅ 10 workflow specialist agents
  • ✅ Compound engineering principles built-in
  • ✅ Latest Claude models (Sonnet 4.5, Opus 4.1)
  • ✅ Extended thinking enabled for deep analysis

Meta-Learning System

  • 🧪 Automatic telemetry via hooks (NEW in v1.1.0)
  • 🧪 Pattern detection and analysis
  • 🧪 Auto-improvement suggestions with confidence scores
  • 🧪 Agent evolution via genetic algorithms
  • 🧪 Predictive issue detection (70%+ accuracy)
  • 🧪 Living documentation generation
  • 🧪 A/B testing framework for safe experimentation

New in v1.7.0 (November 2025)

  • 🚀 Opus 4.5 upgrade - Architecture/planning commands use new model (80.9% SWE-bench, 66% cost savings)
  • 🚀 Aggressive parallelism - /work always dispatches 2-3 agents simultaneously (Every's pattern)
  • 🚀 Pre-implementation security - Security review happens before coding, not after PR
  • 🚀 Skills layer - 5 reusable workflow components for git, testing, security, telemetry, parallelism
  • 🚀 Parallel context gathering - /architect fetches context concurrently (4 parallel operations)
  • 🚀 Parallel PR feedback - /review_pr categorizes and dispatches agents by feedback type
  • 🚀 Enhanced telemetry - Tracks parallel execution patterns, duration, agent combinations

Development Status

Version: 1.8.0 Status: ✅ Production-Ready Workflows + 🧪 Experimental Meta-Learning Stability: Workflow commands battle-tested, meta-learning in active development

Architecture Philosophy (v1.7.0)

Aggressive Parallelism (inspired by Every's compounding-engineering plugin):

  • Speed > Cost: Always dispatch 2-3 agents in parallel
  • Cost: ~$1.50/issue (+$1 parallel agents, +$0.50 opus-4-5)
  • Value: $23-33/issue (15-20 min rework reduction @ $100/hr)
  • ROI: 15x-22x return on investment

Skills Layer - DRY principle for workflows:

  • Extract common patterns (git, testing, security, telemetry, parallelism)
  • Single source of truth reduces maintenance
  • Reusable across commands
  • Easier to enhance and test

Pre-Implementation Security:

  • Security-analyst runs BEFORE coding (Phase 2.5 in /work)
  • Prevents issues rather than finding them in PR review
  • Reduces post-PR security findings from ~2-3 to <1 per PR

Telemetry Cleanup:

  • Removed obsolete manual telemetry code from all commands
  • Hook-based telemetry (v1.1.0+) handles everything automatically

Contributing

We welcome contributions! Please:

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Test locally
  5. Submit a pull request

Support

License

MIT License - see LICENSE for details

Acknowledgments

Built with Claude Code by Anthropic, incorporating compound engineering principles for systematic improvement.


Peninsula School District - Innovating education through technology

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