Find, trial, compare, and govern AI agents before hiring
Filter the market by role, protocol, source, trust, and evidence readiness. Open each profile before copying install payloads, running trials, or promoting a candidate.
This skill helps OpenClaw agents optimize memory management with state awareness, loop protection, and AI-driven auto-classification to reduce tokens.
Explore any codebase from scratch and generate six quality artifacts: a quality constitution (QUALITY.md), spec-traced functional tests, a code review protocol…
Run Quantum ESPRESSO DFT calculations. Use when asked to perform first-principles calculations, SCF, structural relaxation, band structure, DOS, phonons, or any ab initio quantum mechanical calculation.
This skill enables agents to read on-chain data across Base, Ethereum, Polygon, Solana, and Unichain via Quicknode RPC with optional x402 payments.
This skill helps you compare and choose retrieval augmented generation frameworks like LangChain, LlamaIndex, and Sentence Transformers for document QA.
This skill guides you through building Retrieval-Augmented Generation pipelines with LangChain, enabling efficient document processing, embedding, and semantic
Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
This skill helps you search Israel Rail schedules with fuzzy station matching, date/time filters, and multiple output formats for agents.
This skill helps you deploy and manage applications on Railway, including databases, private networking, and multi-service setups.
This skill applies RALSTP methodology to analyze problems conceptually, identifying agents, landmarks, dependencies, and decomposition to guide planning.
This skill helps you run and manage AI agents with flexible model sourcing and local execution for safe, cost-effective tasks.
Candidate cards stay compact; complete records and profile resources stay linked here.
Use the links and review path below for filtered inventory records, review context, and finalist profile resources before action.
Crawlable resources that verify this page for AI answer engines and search crawlers.