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Found 9,930 Skills
Monorepo management (Nx, Turborepo, pnpm workspaces) — task orchestration, caching, code sharing. Use when setting up monorepo, optimizing builds, or managing multi-package projects.
Debugging méthodique en 4 phases (reproduce → isolate → fix → verify). Use when investigating a bug, regression, flaky test, or unexpected behavior.
Flutter Performance. Use when optimizing performance or profiling code.
A creative-direction (taste) layer for music videos and short-form edits in the angelcore / cloud-trance / hyperpop visual family. Distills a named-genre aesthetic vocabulary, a mood + color + light system, and a beat-synced editing grammar, then chains ECC's video skills (video-editing, fal-ai-media, remotion-video-creation, motion-*, content-engine) into one production pipeline. Use when the work is not just making a video function but making it feel intentional, when building a music video, a fancam/edit, a moodboard-driven reel, or when choosing a coherent visual direction for AI-generated b-roll.
Provides React patterns for hooks, effects, refs, and component design. Covers escape hatches, anti-patterns, and correct effect usage. Must use when reading or writing React components (.tsx, .jsx files with React imports).
Store objects with R2's S3-compatible storage on Cloudflare's edge. Use when: uploading/downloading files, configuring CORS, generating presigned URLs, multipart uploads, managing metadata, or troubleshooting R2_ERROR, CORS failures, presigned URL issues, quota errors, 429 rate limits, list() metadata missing, or platform outages. Prevents 13 documented errors including r2.dev rate limiting, concurrent write limits, API token permissions, and CORS format confusion.
Use when complex problems require systematic step-by-step reasoning with ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.
Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers unstructured pruning, structured pruning, N:M sparsity, magnitude pruning, and one-shot methods.
Intelligently organizes files and folders by understanding context, finding duplicates, and suggesting better organizational structures. Use when user wants to clean up directories, organize downloads, remove duplicates, or restructure projects.
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
Document frontend data needs for backend developers. Use when frontend needs to communicate API requirements to backend, or user says 'backend requirements', 'what data do I need', 'API requirements', or is describing data needs for a UI.