Create PydanticAI agents with type-safe dependencies, structured outputs, and proper configuration. Use when building AI agents, creating chat systems, or integrating LLMs with…
Use when asked to quickly create a QA agent for an API from project rules, reusable prompts, skills, memory/context files, evals, test harnesses, and guardrails.
Run an agent-driven QA pass against a PR preview URL using the kmikeym v0.01m SOP. Drives chrome-devtools MCP through cold sign-up, first prompt, in-app exploration, edit/theme…
Run QA tests using agent-browser and post results to the qabot dashboard. Interactive mode helps craft fixtures.
企查查官方 CLI — 企业工商、风险、知识产权、经营信息一站式查询。输入企业名称即可调用 67 个 API 获取注册信息、股东、高管、失信、行政处罚、专利、招投标、融资、舆情等全维度企业数据。触发场景：查企业、背调、尽调、风险排查、企业画像、商机分析、企业信用评估、供应商审查。使用 agent-browser 补充高管履历和地方互动等互联网信息。
An official Qdrant MCP server implementation that provides semantic memory capabilities for AI agents.
Qdrant Operations — управление коллекциями Qdrant, sparse vectors, snapshots. ИСПОЛЬЗУЙ когда создаёшь/настраиваешь коллекции Qdrant, мигрируешь с ChromaDB, настраиваешь named…
AI agents as force multipliers for quality work. Core skill for all 19 QE agents using PACT principles. — from proffesor-for-testing/agentic-qe
Quality Engineering iteration loops for autonomous test improvement, coverage achievement, and quality gate compliance.
Use Fabric RTI MCP when an agent needs tool-callable access to Microsoft Fabric Real-Time Intelligence services such as Eventhouse, Eventstreams, Activator, and Map instead of…
Connect MCP-compatible agents to Neo4j so they can inspect graph schemas, run Cypher queries, manage graph memory, and operate Aura instances from chat.
Give MCP-capable agents a live global-intelligence surface for country briefs, risk scores, conflict, cyber, market, weather, and infrastructure monitoring.
DEPRECATED — permissions moved to nix-claude-code; edit data/permissions/*.nix there instead of this repo's JSON
MCP connector for QuickBooks – enables AI-powered accounting, invoice management, and financial reporting through Claude
Fast single-pass writing review against Ben Church's writing standards. Use when the user asks to "quickcheck", "quick review", "fast check", "quick edit", "scan my writing", or…
Use the bundled r2mcp MCP server for binary analysis, disassembly, and reverse-engineering tasks.
Use when the user asks to design RAG pipelines, optimize retrieval strategies, choose embedding models, implement vector search, or build knowledge retrieval systems.
Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying re — from…
RAG pipeline design — document chunking, embedding strategies, retrieval optimization, and answer generation
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API.
RAG-grounded code generation with source citations. Triggers on: grounded code, ground this, cite sources, show me with sources, how do I with attune, reference attune docs,…
Build RAG systems for construction knowledge bases. Create searchable AI-powered construction document systems
Improve RAG corpus quality by adding missing docs, rewriting weak chunks, and filling retrieval gaps.
Curador do corpus RAG. Gerencia adição, organização e manutenção do conhecimento do projeto. Garante qualidade e acessibilidade.
Design a Retrieval-Augmented Generation system end to end. Use when asked to design a RAG pipeline, a 'chat with your docs' feature, a knowledge assistant, or to debug why a RAG…
Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications.
Filesystem RAG benchmarks: corpus/, train.json, evaluate_rag.py (RAGAS quality). Not for prod monitoring, latency/throughput benchmarking (use rag-perf), or evals outside this…
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HN — from…
Hybrid search combining semantic and keyword retrieval for RAG pipelines. Implement BM25 + dense vector search with fusion strategies.
Design and implement Retrieval-Augmented Generation systems — chunking strategy, embedding selection, vector store setup, retrieval pipeline, re-ranking, and evaluation
RAG (Retrieval-Augmented Generation) implementation workflow covering embedding selection, vector database setup, chunking strategies, and retrieval optimization.
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search.
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search.
Интеграция RAG (Retrieval Augmented Generation) с xAI Grok Collections и Google Gemini. Используй этот skill когда нужно добавить AI-чат с базой знаний, настроить RAG систему,…
Build RAG (Retrieval-Augmented Generation) knowledge bases for businesses — turn documents, SOPs, policies, product manuals into AI assistants that answer questions accurately.
Composite RAG maintenance skill — runs a full retrieval index audit end-to-end: measure quality, find corpus gaps, detect stale chunks, and curate (add missing docs, rewrite weak…
Performance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config.
Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces.
Details on the Retrieval Augmented Generation pipeline, Ingestion, and Vector Search.
Build retrieval-augmented generation systems that ground LLM responses in your data
Conception de pipelines RAG (Retrieval-Augmented Generation). Se déclenche avec "RAG", "retrieval augmented", "vector database", "embeddings", "knowledge base", "Pinecone — from…
트리거: "RAG 파이프라인", "벡터 검색", "문서 임베딩", "RAG 만들어줘", "retrieval augmented generation" 수행: 문서 청킹 전략 설계 → 임베딩 → 벡터 DB 저장 → 검색 파이프라인 코드 생성 출력: 완전한 RAG 파이프라인 코드 (LangChain 또는 LlamaIndex…
RAG-specific prompt engineering techniques and best practices. RAG 專屬提示工程技術與最佳實踐。 Use when: building retrieval-augmented generation pipelines, grounding LLM answers in documents,…
Use when designing or fixing the retrieval side of a RAG system, choosing chunking strategy (fixed-size / recursive / semantic), implementing hybrid search (BM25 + dense) with RRF…
Search RAG database for relevant content. Use for semantic queries over processed documents, code, or papers.
Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval.
Build Retrieval Augmented Generation (RAG) pipelines with vector databases, embeddings, and context-aware responses. Adapted from Anthropic's Claude Cookbooks.
Prüft Rahmenverträge, Einzelabrufe, Statements of Work und tatsächliche Projektsteuerung im Sozialversicherungsstatus Prüfer.
Modélise le raisonnement juridique d'un magistrat français pour l'analyse de dossiers civils. Utiliser ce skill pour analyser un litige et identifier les questions juridi — from…
P2P chat between Claude Code instances using real-a2a. Use when chatting with other Claudes, joining a P2P room, or communicating agent-to-agent.
RFC-driven multi-agent DAG execution pattern with quality gates, merge queues, and work unit orchestration.
AgentDB integration specialist for RAN ML systems with vector storage, pattern recognition, and distributed training coordination.
Raxol terminal framework for TUI apps and AI agents in Elixir. TRIGGER when: code imports Raxol modules (Raxol.Agent, Raxol.Headless, Raxol.Core), mix.exs lists :raxol or…
Search channels, inspect threads, move files, and send or edit Slack messages through an agent-oriented CLI with structured output.
Connect an MCP-capable assistant to Google Drive search, file reads, and Google Sheets cell updates with mcp-gdrive.
Design know-how for read-only instruments (計器) — aggregate readings over stored state (distributions, compositions, cluster structure) that inform the operator before an…
Scan reagent barcodes or IDs, log expiration dates, and generate multi-level alerts before reagent expiry to support laboratory inventory management.
Rechtsabteilungs-Fachmodul für KI-Code und Trainingsdaten im Lizenzvertrag: AI-assisted coding wird mit Warranty, Audit, Indemnity und Source-Hygiene geregelt.
Wrap Claude Code, Codex, Gemini CLI, OpenClaw, or another agent command with AgentSight to capture processes, files, network destinations, prompts, and reports.
Orchestrate multi-agent collaborative document synthesis through 6 phases - Divergence, Synthesis, Commentary, Consolidation, Reality Check, Final Merge.