ai-llm-patterns
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
456 skills found
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Shared memory and collaboration layer for AI coding agents to track actions, manage sessions, detect conflicts, and preserve project context across tools.
Expert tool for auditing and validating the structural integrity, naming conventions, and best practices of Claude Code configurations, including skills, hooks, and commands.
Automate Adobe After Effects tasks using the Model Context Protocol. Manage compositions, layers, keyframes, effects, and expressions for motion graphics, title cards, and logo reveals.
Autonomous iteration loop for AI software development. Executes tasks, validates code, and manages state until completion. Ideal for implementing complex PRP plans.
Fetches Confluence PRDs and transforms them into structured local Markdown for the spec-kit specify workflow, bridging PO handoffs into technical SDD implementation.
A meta-skill for building robust AI agent skills using a TDD approach: define failure (RED), implement the skill (GREEN), and plug rationalization loopholes (REFACTOR).
Audit and optimize your AI prompts with Token Surgeon. Detect 10 common waste patterns, calculate efficiency, and reduce token usage for better prompt performance.
Manage and automate your Bear notes on macOS using the grizzly CLI tool.
Converts PRDs into structured task beads for autonomous execution with ralph-tui, including quality gates and dependency management.
Interactive development workflow manager. Coordinates discovery, planning, review, and build phases using a specialized team of AI agents (Scout, Bob, Garry, Arlo) for consistent project delivery.
Capture and formalize software development ideas into structured design documents within the Hashbrown repository, including research and conceptual sketches.