prompt-lookupVérifiéMCPActivates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use for discovering, retrieving, and improving prompts.CompatibleMCP31 mars 2026Score masque jusqu'a l'inscriptionProtéger mon agent
widget-generatorVérifiéWeb EngineeringGenerate customizable widget plugins for the prompts.chat feed systemCompatible31 mars 2026Score masque jusqu'a l'inscriptionProtéger mon agent
apify-actorizationVérifiéDevOps"Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output."CompatibleAGMCP31 mars 2026Score masque jusqu'a l'inscriptionProtéger mon agent
book-translationVérifiéIDE RulesTranslate "The Interactive Book of Prompting" chapters and UI strings to a new languageCompatible31 mars 2026Score masque jusqu'a l'inscriptionProtéger mon agent
cursor.directoryVérifiéWeb EngineeringConfiguration et règles extraites de pontusab/cursor.directoryCompatible31 mars 2026Score masque jusqu'a l'inscriptionProtéger mon agent
claude-apiVérifiéDocuments"Build apps with the Claude API or Anthropic SDK. TRIGGER when: code imports `anthropic`/`@anthropic-ai/sdk`/`claude_agent_sdk`, or user asks to use Claude API, Anthropic SDKs, or Agent SDK. DO NOT TRIGGER when: code imports `openai`/other AI SDK, general programming, or ML/data-science tasks."CompatibleMCP31 mars 2026Score masque jusqu'a l'inscriptionProtéger mon agent
senior-data-scientistVérifiéDevOpsWorld-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics. Covers A/B testing (sample sizing, two-proportion z-tests, Bonferroni correction), difference-in-differences, feature engineering pipelines (Scikit-learn, XGBoost), cross-validated model evaluation (AUC-ROC, AUC-PR, SHAP), and MLflow experiment tracking — using Python (NumPy, Pandas, Scikit-learn), R, and SQL. Use when designing or analysing controlled experiments, building and evaluating classification or regression models, performing causal analysis on observational data, engineering features for structured tabular datasets, or translating statistical findings into data-driven business decisions.CompatibleAI31 mars 2026Score masque jusqu'a l'inscriptionProtéger mon agent
alpha-vantageVérifiéBackend"Access 20+ years of global financial data: equities, options, forex, crypto, commodities, economic indicators, and 50+ technical indicators."CompatibleAG31 mars 2026Score masque jusqu'a l'inscriptionProtéger mon agent
senior-computer-visionVérifiéGitComputer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom models, optimizing inference, or deploying vision systems.CompatibleAI31 mars 2026Score masque jusqu'a l'inscriptionProtéger mon agent