// AI Reviewed Skills
Skills evaluated and scored by AI for quality and usefulness
Each skill has been evaluated by an AI reviewer on a structured rubric: instruction quality, usefulness, technical soundness, and description precision. Scores range from 0 to 100 — skills scoring 75+ (green badge) are high quality, 50–74 (gold badge) are solid with targeted value.
View Review StatisticsShowing 1-12 of 14122 skills
Generate API documentation from source code, supporting REST APIs, GraphQL, and various documentation formats.
Work with swamp models for AI-native automation. Use when searching for model types, describing model schemas, creating model inputs, running model methods, or viewing outputs. Triggers on "swamp model", "model type", "create input", "type search", "type describe", "run method", "execute method", "model validate", "model delete", "model edit", "model output", "output logs", "CEL expression", or running automation workflows.
Skill for defining coding rules and conventions. Ensures consistent code style and specifies coding standards for AI collaboration. Use proactively when starting a new project or when coding standards are needed. Triggers: convention, coding style, naming rules, 컨벤션, コンベンション, 编码风格, convención, estilo de código, reglas de nombrado, convention, style de codage, règles de nommage, Konvention, Coding-Stil, Namensregeln, convenzione, stile di codice, regole di denominazione Do NOT use for: existing projects with established conventions, deployment, or testing.
Skill for designing and implementing backend APIs. Includes Zero Script QA methodology for validating APIs without test scripts. Use proactively when user needs to design or implement backend APIs. Triggers: API design, REST API, backend, endpoint, API 설계, API設計, API设计, diseño de API, diseño API, diseño de backend, conception API, conception d'API, backend, API-Design, API-Entwurf, Backend, progettazione API, design API, backend Do NOT use for: frontend-only projects, static websites, or Starter level projects.
Git-aware undo by logical work unit (track, phase, or task)
Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, and GCP. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.
Run Python code on cloud GPUs using Modal serverless platform. Use when you need A100/T4/A10G GPU access for training ML models. Covers Modal app setup, GPU selection, data downloading inside functions, and result handling.
Create audiobooks from web content or text files. Handles content fetching, text processing, and TTS conversion with automatic fallback between ElevenLabs, OpenAI TTS, and gTTS.
Use when reviewing sticky navigation, consent banners, chat widgets, skip links, or any fixed-position UI. Validate the actual tab order and viewport behavior at realistic zoom levels.
Work with Obsidian vaults using the official Obsidian CLI (v1.12+). Open, search, create, move, and manage notes from the terminal. Use when working with Obsidian vaults for note management, file operations, searching content, managing tasks, properties, links, plugins, themes, sync operations, or any command-line interaction with Obsidian.
Create free SSH tunnels to expose local ports to the internet using tinyfi.sh. Use when you need to share a locally running app, test webhooks, demo a prototype, or get a public HTTPS URL for any local service — no signup or authentication required.
Create your first Kling AI video generation with a simple example. Use when learning Kling AI or testing your setup. Trigger with phrases like 'kling ai hello world', 'first kling ai video', 'klingai quickstart', 'test klingai'.
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