Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.
Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.
Modular orchestration of agent patterns from Anthropic's engineering guide. Intelligently selects and implements prompt chaining, routing, parallelization, orchestrator-workers,...
Use at end of coding sessions to generate comprehensive session documentation (PROJECT-STATUS.md, NEXT-STEPS.md, LEARNINGS.md) with git commit suggestions and next-session prompts. Wrap up...
Guide for creating specialized Claude Code subagents with proper YAML frontmatter, focused descriptions, system prompts, and tool configurations. Use when the user wants to create a new subagent,...
Implements Doodlestein's iterative review methodology. Contains exact prompts for plan review, beads review, code review, bug hunting, and UI polish. Use when you need to iterate on any artifact...
Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety...
Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety...
Guide for creating custom Claude Code slash commands with proper structure, argument handling, frontmatter configuration, and best practices. Use when the user wants to create slash commands,...
Find opportunities to improve web application code using TanStack libraries (Query, Table, Form, Router, etc.). Avoid man-with-hammer syndrome by applying TanStack after vanilla implementation works.
Find opportunities to improve web application code using TanStack libraries (Query, Table, Form, Router, etc.). Avoid man-with-hammer syndrome by applying TanStack after vanilla implementation works.
Claude Code extensibility: agents, skills, output styles. Capabilities: create/update/delete agents and skills, YAML frontmatter, system prompts, tool/model selection, resumable agents,...
Create, review, and update Prompt and agents and workflows. Covers 5 workflow patterns, runSubagent delegation, Handoffs, Context Engineering. Use for any .agent.md file work or multi-agent system design.
Performs arbitrary-precision arithmetic calculations including addition, subtraction, multiplication, division, and exponents. Use when the user asks to calculate, compute, or evaluate math...
Guides creation of Product Requirements Prompts (PRPs) - comprehensive requirement documents that serve as the foundation for AI-assisted development
Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches...
Enables Claude to use Google AI Studio for testing prompts, exploring models, and prototyping AI applications
Master fine-tuning of large language models for specific domains and tasks. Covers data preparation, training techniques, optimization strategies, and evaluation methods. Use when adapting models...
AI-powered writing assistant for social media content creation. Provides 6 structured writing methods: conversational writing, outline-based writing, completion-style writing, inspiration...