AI Agent Skills Marketplace

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.

Professional API design and review skill for REST, GraphQL, and event-driven architectures.

Evaluates AI coding agent platforms across five structural dimensions that determine real-world performance independently of model quality, so teams select on architectural fit rather than benchmark scores.

RAG fails quietly. It retrieves documents, returns confident-looking answers, and misses the question entirely — because the question required connecting facts across documents, reasoning about sequence, or tracing causation. This skill gives you a five-question diagnostic checklist that classifies any failing query as either RAG-safe or structurally RAG-incompatible, then maps it to the specific failure pattern and the architectural fix that resolves it.

Design, debug, and optimize production RAG systems with expert architecture, hybrid search, and grounding strategies.

Architect, scaffold, and debug production-ready AI agent CLI applications with structured boundaries and packaging.

A pro-grade game development toolkit for Godot 4, Phaser 3, and ECS architectures from prototype to Steam publishing.

Turn plain English app descriptions into fully normalized SQL schemas and entity relationship documentation.

Expert Java code auditor for SE 8–24, flagging performance leaks, threading risks, and modernization gaps.