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Found 3,132 Skills
Self-referential self-improving AI agents that optimize for any computable task using meta-learning and code generation
Install and use World2Agent (W2A) sensors to give AI agents structured, real-time perception of the real world
Build and run durable background coding agents with workflow orchestration, isolated sandboxes, and GitHub integration on Vercel.
Guide for setting up and using Firebase Authentication. Use this skill when the user's app requires user sign-in, user management, or secure data access using auth rules.
Comprehensive guide for Firebase Crashlytics, including provisioning and SDK usage. Use this skill when the user needs help setting up Crashlytics, adding crash reporting, or using the Crashlytics SDK in their application.
Generates a self-contained Python experiment client that uses the ddtrace.llmobs SDK. Emits either a runnable .py script or a Jupyter .ipynb notebook matching the canonical DataDog reference notebook style. Use when the user says "generate Python experiment", "write an SDK experiment", "create a ddtrace experiment", "Python notebook experiment", "use the LLM Obs SDK", or has `ddtrace` installed and wants idiomatic SDK code.
End-to-end pipeline from unlabeled ml_app traces to a bootstrapped evaluator suite. Runs trace classification → root cause analysis → eval bootstrap in sequence with user checkpoints. Use when user says "run the eval pipeline", "go from traces to evals", "bootstrap evals end to end", "classify then RCA then bootstrap", "build an eval set from scratch", or wants a guided walkthrough from production data to evaluator code.
Creates and edits Excel spreadsheets with formulas, formatting, and financial modeling standards. Use when working with .xlsx files, financial models, data analysis, or formula-heavy spreadsheets. Covers formula recalculation, color coding standards, and common pitfalls.
Use when the user wants to build a Python Kafka producer or consumer, add Schema Registry to existing Python code, migrate from raw JSON to schema-backed serialization, or scaffold a confluent-kafka-python project for Confluent Cloud, local Docker, or WarpStream. Also use when user wants to optimize Python Kafka client configuration for WarpStream.
Enforces classNames package usage patterns and Tailwind CSS class ordering conventions in React components. Use this skill whenever writing or reviewing component className props, applying Tailwind classes, using the classnames package, organizing breakpoint-specific styles, writing conditional class expressions, or when the user asks about CSS class ordering, mobile-first responsive patterns, or how to handle className props in components.
Builds territory planning workflows in CARTO combining territory balancing and location allocation. Triggers when the user mentions territory balancing, territory planning, sales territories, service zones, workload distribution, balanced territories, location allocation, facility placement, optimal locations, maximize coverage, minimize cost, minimize travel distance, depot placement, hub placement, warehouse siting, response time optimization, demand coverage, or wants to divide an area into balanced regions or find optimal facility locations.
Guides the user through spatial enrichment workflows — triggered by requests to enrich, add demographics, estimate population around locations, compute spatial features, sociodemographic analysis, "what's around" queries, buffer/isochrone + join patterns, or trade area enrichment.