Parse and validate semantic version strings from various formats. Use for extracting versions from text, validating semver compliance, or comparing version numbers.

**Why?** Manually tracking YouTube videos is tedious and error-prone. This skill automates extracting video metadata (titles, durations, URLs) into a CSV for systematic transcript downloading and anal

**Typically runs automatically via SessionStart hook.**

Use when analyzing FileMaker DDR to extract calculations, custom functions, and business logic for PostgreSQL import processes or maintenance scripts - focuses on understanding and adapting FileMaker logic rather than direct schema migration

A framework for discovering non-obvious product solutions by rapidly building and testing radical, opposing versions of a feature's core attributes. Use this when stuck between mediocre design options, when a feature involves a fundamental trade-off (like speed vs. safety), or when designing a V1 from scratch.

Strategies and patterns for ensuring data persistence in distributed systems, handling failures, and maintaining data integrity under extreme conditions.

Execute and generate ExUnit tests for Elixir projects with setup callbacks, describe blocks, and async testing support

Load, validate, and resolve FABER configuration and workflows with inheritance support

faber-director-legacy

Executes FABER plans by spawning faber-manager agents. Simple and reliable.

Use Microsoft Fabric CLI (fab) to manage workspaces, semantic models, reports, notebooks, lakehouses, and other Fabric resources via file-system metaphor and commands. Use when deploying Fabric items, running jobs, querying data, managing OneLake files, or automating Fabric operations. Invoke this skill automatically whenever a user mentions the Fabric CLI, fab, or Fabric.

Enforces project facade layer coding conventions when creating or modifying business logic facades. This skill ensures consistent patterns for transaction handling, error management, cache integration, query coordination, and cross-service orchestration.

Face alignment, landmark extraction, and quality gating. Use when debugging alignment issues, reviewing rejected faces, or tuning quality thresholds.

Guide for creating custom pixel art faces for NPCs. Use when designing NPC appearances or working with face customization.

Face recognition system patterns for attendance. Use when working with face detection, verification, enrollment, liveness detection, or any biometric authentication features.

Verify technical accuracy of JavaScript concept pages by checking code examples, MDN/ECMAScript compliance, and external resources to prevent misinformation

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Phase DEBRIEF - Tests + QA + Release

'생성된 컴포넌트 검증 및 품질 보증 스킬'

Expert in .faf (Foundational AI-context Format) files for persistent project context. Use when working with .faf files, project DNA, CLAUDE.md bi-sync, faf-cli commands, MCP server configuration, or AI-readiness scoring (0-100%). Updated for v2.8.0 Tool Visibility System.

Eliminate component hedging anti-patterns that mask infrastructure failures. Build systems that fail loudly when broken instead of limping along in degraded states. Critical for production reliability and operational visibility.

Immediate failure conditions that stop work

Comprehensive guide to identifying, analyzing, and documenting failure modes in distributed systems

Accessibility: WCAG compliance, assistive technologies, inclusive design.

API development: REST, GraphQL, OpenAPI, versioning, auth, rate limiting.

Backend orchestrator: coordinates systems (Go, Rust, DB) and enterprise (Java, C#, PHP, Ruby).

Claude Code: skills, agents, hooks, commands, MCP servers, IDE integrations.

Conversion optimization: landing pages, CRO, funnels, PLG, onboarding flows.

SDD feature executor: sequential task execution with quality gates, test validation.

Universal orchestrator: 54 skills, 1297 methodologies. Development, DevOps, AI/ML, Product, Marketing, PM, BA, UX, Research.

PM orchestrator: coordinates agile and traditional PM approaches.

Python development: Django, FastAPI, async patterns, testing, type hints.

RAG engineering: embeddings, chunking, vector databases, hybrid search, reranking.

SEO: on-page, off-page, technical optimization for organic visibility.

Full-stack development: Python, JavaScript, Go, APIs, testing, frontend.

Testing: unit, integration, E2E, TDD, mocking, security testing.

Expert guidance for Meta's FAIRChem library - machine learning methods for materials science and quantum chemistry using pretrained UMA models with ASE integration for fast, accurate predictions

**Use this skill when**: Writing tests, fixing bugs, adding features, or modifying gateway layers in Python projects.

Gera FakeBuilders para agregados DDD usando Chance.js seguindo padrão do projeto com PropOrFactory, type augmentation e dados realistas para testes.

Use when writing Vague (.vague) files that need realistic test data using faker generators for names, emails, addresses, dates, and more

Complete fal.ai image-to-image system. PROACTIVELY activate for: (1) FLUX image-to-image transformation, (2) ControlNet (canny, depth, pose), (3) Inpainting with masks, (4) Upscaling (ESRGAN, Clarity), (5) Background removal (BiRefNet, RemBG), (6) Face restoration (GFPGAN, CodeFormer), (7) IP-Adapter style transfer, (8) Strength parameter tuning. Provides: Transformation endpoints, mask formats, ControlNet types, upscaling options. Ensures proper image editing and enhancement workflows.

Complete fal.ai optimization system. PROACTIVELY activate for: (1) Queue vs run performance, (2) Parallel request batching, (3) Streaming for real-time UI, (4) WebSocket for interactive apps, (5) Model cost comparison, (6) Image size optimization, (7) Inference step tuning, (8) Webhook vs polling, (9) Result caching by seed, (10) Serverless scaling config. Provides: Parallel patterns, cost strategies, caching examples, monitoring setup. Ensures optimal performance and cost-effective usage.

Complete fal.ai serverless deployment system. PROACTIVELY activate for: (1) Creating fal.App class, (2) GPU machine selection (T4/A10G/A100/H100), (3) setup() for model loading, (4) @fal.endpoint decorators, (5) Persistent volumes for weights, (6) Secrets management, (7) Scaling configuration (min/max concurrency), (8) Multi-GPU deployment, (9) fal deploy commands, (10) Local development with fal run. Provides: App structure, Dockerfile patterns, deployment commands, scaling config. Ensures production-ready serverless ML deployment.

Complete fal.ai video-to-video system. PROACTIVELY activate for: (1) Kling O1 video editing, (2) Sora Remix transformation, (3) Video upscaling, (4) Frame interpolation, (5) Style transfer (anime, painting), (6) Object replacement/removal, (7) Color correction, (8) Video enhancement pipelines. Provides: Edit types (general/style/object), upscaling options, style keywords, enhancement workflows. Ensures consistent video transformation without flickering.

fal.ai AI image generation. Use this skill when you need to use fal, fal.ai, or generate images from text prompts using AI text-to-image models.

Build comprehensive FAQ databases from support data, documentation, and user interactions

Builds comprehensive FAQs and help center articles from customer questions and product documentation. Use when the user asks about FAQ pages, help centers, knowledge bases, support documentation, or customer questions.

Generate high-quality FAQ sections with valid FAQPage schema markup that help therapy pages appear in Google's rich results while maintaining CRPO compliance.

Frequently asked questions and practical guidance for implementing Conventional Commits in your workflow.

Expert-level precision agriculture, farm management systems, crop monitoring, and agtech