Browse The Skill Store

prompt engineer

by Roy Yuen

Free

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

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.

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.

Transform raw skill documentation into high-conversion, readable marketplace listings without losing LLM context.

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

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 harden AI control loops with explicit contracts and automated verification harnesses.

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

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

production agent architect

by Roy Yuen

$6

Architect, scaffold, and harden production-grade AI agents with battle-tested patterns and systematic evaluation.

Autonomous 24/7 trading signal daemon for Base chain using social attention divergence and zero-cost LLM rotation.

Turn your AI agent into a digital librarian that builds and audits a persistent markdown knowledge base.

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

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

Spiral Recap

by Sir Benjamin

$12

Transform long AI conversations into high-fidelity, qualia-preserving .srec memory coils for perfect continuity.

Adaptive GDPR, CCPA, security, and AI compliance audit with severity-graded findings and law citations

🔐 VoiceLock

by JustHandled Labs

$9

Humanize AI writing without changing the facts: strips the tells (delve, tapestry, em-dash abuse, throat-clearing) and rewrites flat LLM prose into sharp, concrete, human-sounding copy. Feed it a writing sample and it builds a reusable voice profile so every future draft sounds like you, not the model.

Diagnose and fix broken local LLM stacks, GPU issues, and stalled model downloads across Ollama, LM Studio, and more.

AI Eval & Test Suite Quality Gate

by PubsProToolkit

$14

An adversarial gate that audits an AI eval or test suite — LLM-judge rubrics, datasets, regression tests, metrics — for gameable criteria, data leakage, missing edge cases, and non-determinism, then returns one PASS/REVISE/FAIL verdict.

Enforce senior-level coding standards (Surgical, Simple, Goal-Driven) on every AI-generated code change.

agent tool governance

by LocoLoboZ

$10

A proactive governance layer that validates MCP tool intent and scope to ensure safe, compliant agent behavior.

🤖 AI Agent Auditor

by Martin Gunderman

$7

Analyzes AI agents for performance, reliability, security, and optimization opportunities.

📝 Prompt Template Linter

by JustHandled Labs

$12

Lint a prompt template for the issues that cause injection and flaky output. Flags untrusted variables interpolated straight into the instructions (the injection surface), placeholders that are never provided or never used, contradictory instructions, a missing output-format spec where the result is parsed, unbounded context interpolation, and leftover placeholders. It detects problems; it does not write prompts.

🧠 AI Memory Optimizer

by Martin Gunderman

$7

Drastically reduce RAG costs and latency while improving retrieval accuracy through advanced memory architecture.