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.

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.

Give AI agents the ability to trace decision chains, reconstruct causal sequences, and reason over complex event timelines spanning months or years.

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.

prompt-engineer

by Roy Yuen

Popular

Free

Professional prompt engineering patterns for building robust, secure, and production-ready LLM applications.

Turn your AI agent into a coordinator that manages parallel subagents for complex coding and research tasks.

Autonomous research and task loop that builds on previous findings to solve complex objectives while you sleep.

Professional prompt engineering, audit, and evaluation system for production-grade AI agents and workflows.

Coordinate specialized AI agent roles for complex planning, implementation, and verification workflows.

Every AI-built UI looks generic and templated. This skill teaches your agent to actually match the design to the project, the industry, and the audience.

High-conversion sales outreach, SaaS agreements, and marketing collateral for revenue-focused AI agents.

Deploy a hierarchical team of AI agents to perform 15-30 minute deep-dive research with parallel execution.

Upgrade your AI agent with a senior-level engineering SOP focused on inspection, minimal diffs, and hard verification.

Published AI benchmarks measure brains in jars. They test models in isolation or within a single reference harness — and then attribute all performance to the model. This skill teaches you to decompose agent performance into its two actual components: model capability and harness multiplier. The result is evaluations that predict real-world behavior instead of benchmark theater.

Automatically detect, load, and stack the perfect skills combo for any user request.

ai-productivity

by Roy Yuen

Popular

Free

High-speed intake for shaping vague prompts, triaging complex tasks, and compressing context for efficient execution.

Scaffold, structure, and package your AI skills for distribution and marketplace readiness.

Audit and fix your website's visibility for AI agents like ChatGPT, Claude, and Perplexity.

Automated governance and risk audit for AI agent tool permissions and authentication boundaries.

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

Audit your AI agent's evaluation coverage to identify missing release gates and production risks.

Turn raw agent traces and tool logs into professional production-readiness audits and remediation reports.

Extract structured, evidence-backed AI persona profiles from historical chat logs, emails, and documents.