Loading...
Loading...
Found 28 Skills
This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
Lead coordinator that orchestrates 5 news scraper agents in parallel to gather headlines from 15 top business news websites
Review a single file or all files in a folder for data inconsistencies, reference errors, typos, and unclear terminology using parallel sub-agents
Automatically fix ESLint errors by modifying code to comply with linting rules. For small codebases (≤20 errors), fixes directly. For larger codebases (>20 errors), spawns parallel agents per directory for efficient processing. Never disables rules or adds ignore comments.
Transcribes video audio using WhisperX, preserving original timestamps. Creates JSON transcript with word-level timing. Use when you need to generate audio transcripts for videos.
Illustre automatiquement le journal d'une aventure BFRPG en générant des images pour les moments clés (combats, explorations, découvertes). Utilise la génération parallèle pour une performance optimale.
Self-contained parallel generator — invoke directly, do not decompose. Generates 3-10 app variations in parallel for comparing ideas. Use when user says "explore options", "give me variations", "riff on this", "brainstorm approaches", or wants to see multiple interpretations of a concept.
Analyze OpenCode conversation history to identify themes and patterns in user messages. Use when asked to analyze conversations, find themes, review how a user steers agents, or extract insights from session history.
Invokes Google Gemini models for structured outputs, multi-modal tasks, and Google-specific features. Use when users request Gemini, structured JSON output, Google API integration, or cost-effective parallel processing.
Fan out a prompt to multiple AI coding agents in parallel and synthesize their responses.
Fix all ESLint and TypeScript errors with parallel processing using snipper agents
Worker that runs parallel external agent reviews (Codex + Gemini) on Story/Tasks. Background tasks, process-as-arrive, critical verification with debate. Returns filtered suggestions for Story validation.