rag-implementation
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
437 skills found
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Generates a random lucky number between 0 and 9999 for games, decision-making, or entertainment.
A framework for applying Test-Driven Development to process documentation, ensuring agent reliability by using pressure scenarios to identify and patch rationalization loopholes.
Enforces a strict evidence-before-assertion protocol for coding agents, requiring fresh command-line verification output before any claim of completion, success, or bug fixes.
Real-time e-commerce price comparison and coupon hunting across major Chinese platforms like Taobao, JD, Pinduoduo, and more.
Expert-level guidance for ffuf web fuzzing, enabling automated discovery of hidden directories, files, parameters, and vulnerabilities during penetration testing.
Expert Rust analysis for ownership, borrowing, and lifetime errors, including E0382, E0597, and memory safety patterns.
AI-optimized artifact tracking system for token-efficient project orchestration, phase management, and automated task delegation using YAML-Markdown hybrid formats.
Implement robust backend error handling with custom classes, middleware, structured logging, and recovery patterns.
Automated OpenClaw repository maintainer: triage, label, and validate PRs/issues using gitcrawl and GitHub CLI.
Audit, prune, and maintain vector memory for Clawdbot. Prevents token waste, clears junk data, and automates memory hygiene via LanceDB maintenance.
Automated inbound and outbound AI email workflow for 0 Finance, enabling agents to manage invoices, bank transfers, and financial conversations.