MLOps
Operacions d’aprenentatge automàtic
senior-data-engineer
nimeshgurung
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, or implementing data governance.
cohere-streaming
RSHVR
Cohere streaming reference for real-time text generation, tool use events, and RAG citations. Covers all stream event types and async streaming patterns.
video-gen
maxgent-ai
AI video generation with text-to-video, image-to-video, and first/last frame control. Use when users ask to generate or create videos from text prompts or images.
V-JEPA 2 Self-Supervised Training
sovr610
This skill should be used when the user asks to "train V-JEPA model", "implement JEPA pretext task", "set up EMA target encoder", "configure self-supervised training", "implement smooth L1 loss", "create training loop for V-JEPA", "optimizer configuration", "learning rate schedule", "warmup cosine decay", "EMA momentum schedule", "collapse prevention", "predictor architecture", "masked prediction loss", "DROID fine-tuning loop", "annealing phase", "cooldown training", or needs guidance on V-JEPA 2 self-supervised learning, training loops, predictor design, or optimization strategies.
Visualization & Interpretability
sovr610
This skill should be used when the user asks to "visualize activations", "plot spike rasters", "show attention heatmaps", "visualize workspace", "plot reasoning traces", "create t-SNE embeddings", "interpret model decisions", "visualize HTM patterns", "show neuromodulator levels", "plot training curves", "create activation maps", "visualize feature maps", "explain predictions", "debug model behavior visually", or needs guidance on visualization, interpretability, or explainability tooling for the brain_ai system.
senior-ml-engineer
nimeshgurung
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.
groq-api
diskd-ai
Groq API integration for building AI-powered applications with ultra-fast LLM inference. Use when working with Groq's Chat Completions API, Python SDK (groq), TypeScript SDK (groq-sdk), tool use/function calling, vision/image processing, audio transcription with Whisper, streaming responses, text-to-speech, content moderation with Llama Guard, batch processing, or any Groq API integration task. Triggers on mentions of Groq, GroqCloud, or fast LLM inference needs.
agentic-development
campbellmcgregor
Conversational guidance for building software with AI agents, covering workflows, tool selection, prompt strategies, parallel agent management, and best practices based on real-world high-volume agentic development experience. Use this skill when users ask about setting up agentic workflows, choosing models, optimizing prompts, managing parallel agents, or improving agent output quality.
feedback-mastery
VisualxIntelligence
Navigate difficult conversations and deliver constructive feedback using structured frameworks. Covers the Preparation-Delivery-Follow-up model and Situation-Behavior-Impact (SBI) feedback technique. Use when preparing for difficult conversations, giving feedback, or managing conflicts.
rails-testing-rspec
shivamsinghchahar
Write Rails tests with RSpec, FactoryBot, and mocking patterns. Use when creating tests, writing specs for models/controllers/requests, setting up test fixtures, or mocking external services.
Audio Transcriber
yousufjoyian
Claude agent skills and workspace configuration
aidr
pc-style
Offload context-heavy but low-complexity codebase work to Aider through a thin CLI wrapper. Use when another AI agent should avoid loading large repository context for tasks like discovery, repetitive refactors, cross-file version bumps, and broad search/explain passes. Supports safe read-only scanning, scoped edit runs, model-mode routing, and setup/model diagnostics.
prompt-engineer
pateljig4545
Transform rough prompts/ideas into production-ready LLM prompts. Use when crafting, refining, or optimizing prompts for any AI model (Claude, GPT, Llama, etc.) with advanced techniques like CoT, constitutional AI, RAG optimization.
capa-officer
nimeshgurung
Senior CAPA Officer specialist for managing Corrective and Preventive Actions within Quality Management Systems. Provides CAPA process management, root cause analysis, effectiveness verification, and continuous improvement coordination. Use for CAPA investigations, corrective action planning, preventive action implementation, and CAPA system optimization.
SKILL.md — task-router
manthis
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senior-data-scientist
nimeshgurung
World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
streams-mcp-tools
jwongmongodb
Build, operate, and debug Atlas Stream Processing through the MongoDB MCP Server. Use when user says "set up a Kafka pipeline", "deploy a stream processor", "add a connection to my workspace", "why is my processor failing", "stop my processor", "delete my workspace", "show me my Streams workspaces", or any task involving Atlas Stream Processing workspaces, connections, or processors. Do NOT use for general MongoDB queries, Atlas cluster management, or non-Streams Atlas operations.
discuss
joshuajbrunner
Explicitly launch and conduct a substantive discussion with one or more pi sessions through Herdr and pi-intercom.
ai-news-radar
HUANGYming
Summarize current AI news by searching for recent developments across model releases, product launches, research, regulation, funding, and major industry moves. Use when the user wants a concise snapshot of what is happening in AI right now.
token-cost
EvilFreelancer
Use when the user invokes /token-cost or asks for the floor / bedrock / self-cost / "real" price of LLM tokens on a self-hosted server — the physical lower bound from electricity plus hardware amortization, NOT the market API price. The skill measures power draw and generation speed ON the server (nvidia-smi, streaming benchmark) and asks for electricity tariff, hardware cost and amortization period, then prints cost per 1M input/output tokens. Triggers: "сколько на самом деле стоит токен", "цена самохоста", capacity and break-even planning.
openclaw-groq-orpheus-tts
ahmedeid5
Fast and FREE Arabic (Saudi) & English AI voices. Generous 100 requests per day via Groq API. Professional, high-quality generative TTS using Orpheus models.
Inference Optimization
sovr610
This skill should be used when the user asks to "optimize inference", "speed up predictions", "add caching", "batch inference", "async inference", "reduce inference latency", "profile inference", "memory efficient inference", "inference pipeline", "warm up model", "KV cache", "inference throughput", "latency benchmark", "optimize forward pass", or needs guidance on inference performance optimization, caching strategies, batch processing, async execution, or latency profiling for the brain_ai system.
Sleep Consolidation Cycle (Offline Replay + Synaptic Homeostasis + Systems Consolidation)
sovr610
This skill should be used when the user asks to "add sleep cycle", "memory consolidation", "offline replay", "synaptic homeostasis", "sleep-wake cycle", "memory replay consolidation", "sharp wave ripple replay", "slow wave sleep computation", "dream-like generative replay", "synaptic downscaling", "interleaved replay", "systems consolidation", "hippocampal-cortical transfer", "offline training phase", "implement sleep consolidator", "add NREM replay phase", "add REM generative phase", "implement experience replay scheduler", "add weight downscaling", "implement complementary learning systems", "add fast-to-slow transfer", "implement two-phase training", "add sleep phase to training orchestrator", "implement priority replay sampling", "add compressed replay", "implement dream replay from world model", "add pseudo-rehearsal", "implement capacity restoration", "add synaptic renormalization", or mentions sleep consolidation, offline consolidation phase, NREM structured replay, REM creative recombination, sharp-wave ripple compressed replay, synaptic homeostasis hypothesis, Tononi-Cirelli downscaling, complementary learning systems, hippocampal-cortical transfer, fast-to-slow knowledge distillation, dream-like generative replay, pseudo-experience generation, two-phase wake-sleep training, replay priority sampling, capacity restoration, or sleep-wake integration with training orchestrator in the cognitive pipeline.
database-migrations
Dsantiagomj
Database schema migrations and change management. Covers Prisma migrations, schema versioning, rollback strategies, and safe production deployments. Trigger: When creating database migrations, when modifying schemas, when deploying database changes, when handling rollbacks.