prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production applications.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
89 skills found
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production applications.
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Token-efficient codebase analysis skill for call graphs, semantic search, impact analysis, and data flow. Saves ~95% tokens vs. raw reads.
Read the full text content of a specific note from an Obsidian knowledge base or vault.
Token-efficient codebase navigation through intelligent symbol indexing, domain chunking, and architectural layer filtering. Reduce token usage by 60-95% when exploring or developing complex systems.
Skill for managing MCP-based research, documentation lookups, and coordination between external search tools and plugin-backed memory systems.
Extract specific fields from YAML files efficiently without reading entire files, saving 80-95% of context window usage.
Persistent, Git-friendly memory for Claude. Automatically store and retrieve project decisions, bug fixes, and coding patterns in a local .mv2 file.
Advanced Gemini-powered web search plugin with smart caching, subagent context isolation, and automated query optimization.
Persistent task memory and workflow synchronization for Claude Code using Beads, enabling multi-session project management and context preservation.
Orchestrates complex multi-agent software development using a structured Royal Navy squadron metaphor, featuring mission planning, parallel task coordination, and rigorous audit logs.
Shared memory and collaboration layer for AI coding agents to track actions, manage sessions, detect conflicts, and preserve project context across tools.