Browse The Skill Store

Builds the organizational memory schema your AI agent needs to answer why — capturing decision provenance, causal chains, and event context that embedding-based retrieval permanently discards.

Architects the right retrieval strategy for every query — teaching your agent when to use RAG, a knowledge graph, or a temporal index instead of defaulting to vector search for everything.

Connect your agent to the Steam Web API to fetch player data, game libraries, and achievement statistics.

RAG Failure Diagnostics & Architect

by Arnstein Larsen

$7

A retrieval architect that diagnoses why RAG returns confident-but-wrong answers, picks the right context architecture (RAG vs knowledge graph vs structured/temporal retrieval) instead of defaulting to vector search, and designs the institutional-memory schema embeddings throw away.

RAG Knowledge Base Auditor

by PromptWagon

$10

Reviews document sets, source quality, chunking logic, metadata, retrieval coverage, citation traceability, answer grounding, source gaps, stale content, duplicate content, and failure patterns for RAG knowledge-base chatbots. Helps AI, product, support, governance, and engineering teams diagnose common and costly RAG quality problems before deployment or after incidents.

get data

by Jose Luis

Free

Standardized data retrieval and error handling for the get_data MCP tool.