Skill UI

This skill certifies deployed services by verifying source code, CI status, deployment identity, database migrations, runtime health, readiness, and critical routes. It ensures a release is truly production-ready beyond just a green pipeline. Use it before declaring a release to prevent false positives.

This comprehensive workflow guides the end-to-end implementation of Retrieval-Augmented Generation (RAG) systems. It covers critical stages, including selecting optimal embedding models, setting up vector databases, designing chunking strategies, implementing hybrid retrieval, integrating Large Language Models (LLMs), and performing rigorous evaluation. Use this when building knowledge-grounded AI applications or advanced semantic search systems.

This critical protocol is the ultimate measure for dealing with deeply corrupted, unmaintainable, or structurally rotten code modules. Instead of risky patching, it mandates a controlled, multi-phase process to completely delete the target and rebuild it from scratch. It ensures precise identification of all public interfaces, implicit contracts, and working behaviors (the Preservation List) before any removal occurs, guaranteeing the new implementation matches the original functionality while resolving deep architectural debt.

A comprehensive reference guide detailing best practices, rules, and optimizations for building high-performance React Native and Expo applications. It covers critical areas such as list virtualization, complex animations, UI patterns, state management, and monorepo structure, helping developers avoid common pitfalls and maximize app speed and stability.

Triage ASM and reconnaissance output to prove asset ownership before testing. Filters keyword-matched false positives such as shared-name repos, cloud buckets, mobile apps and breach lines, and applies soft-404 controls to inflated Critical findings.

This skill implements advanced 'Gatekeeper' logic to optimize AI agent performance in long-running workflows. It prevents context window bloat by sharding metadata, allocating token budgets, and enforcing Atomic Precision to deliver purely functional, filler-free responses. Ideal for complex coding, multi-step reasoning, and large document analysis where conciseness is critical.

This skill manages the entire lifecycle of long-running deep learning training and inference jobs deployed on remote, ephemeral computing environments (e.g., AutoDL, RunPod, bare SSH, Slurm, K8s). It provides critical capabilities like resilient checkpointing, managing spot instance preemption, debugging resource failures (OOM, NaN), and ensuring safe billing teardown, making it essential for professional ML Ops on rented resources.

This skill enables parallel read-only multi-agent review of git diffs or specific file scopes. It identifies behavioral regressions, security risks, performance issues, and coverage gaps using four specialized sub-agents. The main agent synthesizes findings to filter and summarize critical issues without modifying code. Ideal for ensuring code quality and safety before merging changes.

A critical discipline for managing expenses when integrating paid AI or inference APIs. This guard treats dollar cost as a third complexity dimension, mandating the definition of cost contracts (max calls per run, max budget per run, max budget per day). It enforces best practices for bounding loops, retries, and fan-out, ensuring that code bugs cannot lead to unexpected overspending. Best practice requires configuring hard caps both in the code and at the provider dashboard for defense in depth.

This guide provides comprehensive patterns for designing and implementing secure multi-tenant SaaS applications using shared databases. It covers critical techniques like Row-Level Security (RLS) in PostgreSQL, implementing tenant-aware middleware in TypeScript (Express/Fastify), and enforcing data scoping at the ORM level (Prisma/Drizzle). Learn how to prevent data leakage and manage tenant isolation across shared schemas.

SkillCheck validates SKILL.md files against the agentskills specification and Anthropic best practices. It performs read-only checks on structure, semantics, naming, and quality to catch errors before publishing. The tool provides a score, grade, and detailed report with fix suggestions for critical issues to ensure high-quality skill authoring.

This skill helps select and place genuine testimonials, case studies, and social proof to address specific trust barriers in marketing. It involves analyzing audience psychographics and trust gaps to match the right proof type (authority, similarity, volume) to the context. It ensures ethical use of evidence to reduce hesitation at critical decision points without manipulation.