Claude Code Plugin Marketplace

A collection of Claude Code plugins for productivity and learning workflows.

Available Plugins

mochi-creator

Version 1.1.0 - Create evidence-based spaced repetition flashcards using cognitive science principles from Andy Matuschak's research.

What Makes This Different: This plugin doesn't just create flashcards—it applies research-backed principles to ensure cards actually work for long-term retention. Based on Andy Matuschak's extensive work on spaced repetition and retrieval practice.

Core Features:

• Quality Validation: Checks prompts against 5 properties (focused, precise, consistent, tractable, effortful)
• Evidence-Based Design: Applies cognitive science principles to every card
• Knowledge-Type Workflows: Specialized patterns for factual, conceptual, procedural, and salience prompts
• Anti-Pattern Detection: Identifies and fixes common mistakes (binary questions, unfocused prompts, vague language)
• 5 Conceptual Lenses: Creates robust understanding through multiple angles (attributes, similarities, parts, causes, significance)
• Procedural Patterns: Focus on transitions, rationale, and timing instead of rote memorization
• Interactive Creation: Guided workflows with quality checks at every step
• Template Support: Build reusable card formats with custom fields
• Deck Management: Hierarchical organization and batch operations

Requirements:

• Mochi.cards account and API key
• Python with requests library

Installation:

# Add this marketplace
/plugin marketplace add joshuaoliphant/claude-plugins

# Install the plugin
/plugin install mochi-creator@oliphant-plugins

Setup:

Set your Mochi API key as an environment variable:

export MOCHI_API_KEY="your_api_key_here"

To get your API key:

1. Open Mochi.cards application
2. Navigate to Account Settings
3. Find the API Keys section
4. Generate a new API key

Quick Start:

Here's the simplest way to get started—create flashcards about a basic concept:

1. Set your API key: export MOCHI_API_KEY="your_api_key_here"
2. Invoke the plugin: "Create Mochi cards to help me understand what recursion is"
3. Get evidence-based flashcards: Cards appear in your Mochi deck with focused, atomic prompts

That's it! The plugin handles quality validation and cognitive science principles automatically.

Usage Examples:

Simple requests:

• "Create Mochi cards about dependency injection" → Creates 5-8 focused, atomic cards
• "Turn this conversation into flashcards" → Extracts key concepts with quality validation
• "Help me create flashcards for learning React hooks" → Interactive workflow with guidance

Advanced workflows:

• "Create conceptual cards for TDD using the 5 lenses approach" → Attributes, similarities, examples, causes, significance
• "Make procedural cards for git workflow focusing on transitions and rationale" → No rote steps, emphasis on understanding
• "Create factual cards from this recipe" → Breaks into atomic prompts automatically

Quality-focused:

• Claude will proactively validate prompts and suggest improvements
• Detects unfocused prompts: "This tests 3 details - let me split into separate cards"
• Identifies anti-patterns: "This is a binary question - let me rephrase as open-ended"
• Applies knowledge-type appropriate patterns automatically

The "More Than You Think" Rule: The plugin encourages creating 3-5 focused cards instead of 1 comprehensive card. Each focused prompt takes only 10-30 seconds across an entire year of review, but creates much stronger, more reliable memories.

Research Foundation:

This plugin is built on cognitive science research including:

• Retrieval Practice (Roediger & Karpicke, 2006): Active recall strengthens memory more than passive review
• Spacing Effect (Ebbinghaus, 1885; Cepeda et al., 2006): Distributed practice beats massed practice
• Elaborative Encoding (Craik & Lockhart, 1972): Deeper processing creates stronger memories
• Desirable Difficulties (Bjork, 1994): Optimal learning occurs with moderate challenge
• Andy Matuschak's extensive work on prompt design and spaced repetition systems

The 5 properties framework, knowledge-type patterns, and quality validation are all grounded in this research to ensure cards that actually work for long-term retention.

adw-bootstrap

Version 1.0.0 - Bootstrap AI Developer Workflows (ADWs) infrastructure in any codebase enabling programmatic agent orchestration.

What It Does: Transforms regular projects into ones where AI agents can be invoked programmatically to plan, implement, test, and deploy features. Uses intelligent adaptation to fit any project structure, language, or framework.

Core Features:

• Programmatic Agent Execution: Execute prompts via subprocess or SDK
• Progressive Enhancement: Three setup phases (Minimal → Enhanced → Scaled)
• Intelligent Adaptation: Analyzes target project and adapts patterns to fit conventions
• Upgrade Support: Safely upgrade existing setups to higher phases with automatic backups
• Reusable Templates: Slash command templates for common workflows
• Multi-Phase Workflows: Orchestrate plan → implement → test → deploy sequences
• Structured Observability: Agent outputs tracked in agents/{id}/ directories
• Three Model Support: Haiku (fast), Sonnet (balanced), Opus (max intelligence)
• Git Worktree Isolation: Scaled phase includes isolated development environments
• State Management: Persistent state across workflow phases
• GitHub Integration: Issue tracking, PR creation, automated workflows

Setup Phases:

Minimal (Always installed):

• Core subprocess execution
• Basic CLI (adw_prompt.py)
• Essential slash commands (chore, implement)
• Structured output directories

Enhanced (Recommended for development):

• SDK-based execution with type safety
• Interactive session support
• Compound workflows (plan + implement in one command)
• Richer slash command library

Scaled (Production/teams):

• State management (adw_state.json)
• Git worktree isolation in trees/ directories
• GitHub integration (gh CLI)
• Multi-phase SDLC workflows
• 20+ advanced slash commands

Installation:

# Add this marketplace
/plugin marketplace add joshuaoliphant/claude-plugins

# Install the plugin
/plugin install adw-bootstrap@oliphant-plugins

Usage Examples:

Bootstrap new projects:

• "Set up ADWs" → Analyzes project and creates appropriate infrastructure
• "Bootstrap agentic workflows" → Detects language, framework, and adapts setup
• "Initialize ADW infrastructure" → Recommends setup phase based on project maturity

Upgrade existing setups:

• "Upgrade my ADWs to enhanced" → Adds SDK support and compound workflows
• "Upgrade to scaled ADWs" → Adds state management and worktree isolation
• "Add scaled capabilities" → Safely adds features with automatic backups

After setup:

• ./adws/adw_prompt.py "implement feature X" → Direct prompt execution
• ./adws/adw_prompt.py "quick check" --model haiku → Fast economical execution
• ./adws/adw_chore_implement.py "add logging" → Plan + implement workflow
• ./adws/adw_sdlc_iso.py 123 → Complete SDLC for issue #123 (scaled phase)

Philosophy:

The skill uses "intelligence over templating" - it reads working reference implementations, analyzes your project structure, and intelligently adapts patterns to fit your conventions. No rigid string substitution.

Progressive Enhancement:

Start minimal (5 files) and add capabilities as needed. Clean upgrade path with safety backups ensures you never lose customizations.

Contributing

Contributions are welcome! Feel free to submit issues or pull requests.

License

MIT