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Found 1,619 Skills
MUST READ before creating or enhancing any ADK agent project. Use when the user wants to build a new agent (e.g. "build me a search agent") or enhance an existing project (e.g. "add CI/CD to my project", "add RAG").
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.
Use this skill when encountering errors, bugs, performance issues, or unexpected behavior in an InsForge project — from frontend SDK errors to backend infrastructure problems. Trigger on: SDK returning error objects, HTTP 4xx/5xx responses, edge function failures or timeouts, slow database queries, authentication/authorization failures, realtime channel issues, backend performance degradation (high CPU/memory/slow responses), edge function deploy failures, or frontend Vercel deploy failures. This skill guides diagnostic command execution to locate problems; it does not provide fix suggestions.
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
DigitalOcean Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents on GPU infrastructure with foundation models, knowledge bases, and agent routes. Use when planning or operating AI agents on DigitalOcean.
Provides AWS Lambda integration patterns for Python with cold start optimization. Use when deploying Python functions to AWS Lambda, choosing between AWS Chalice and raw Python approaches, optimizing cold starts, configuring API Gateway or ALB integration, or implementing serverless Python applications. Triggers include "create lambda python", "deploy python lambda", "chalice lambda aws", "python lambda cold start", "aws lambda python performance", "python serverless framework".
Build applications with InsForge Backend-as-a-Service. Use when developers need to: (1) Set up backend infrastructure (create tables, storage buckets, deploy functions, configure auth/AI) (2) Integrate InsForge SDK into frontend applications (database CRUD, auth flows, file uploads, AI operations, real-time messaging) (3) Deploy frontend applications to InsForge hosting IMPORTANT: Before any backend work, you MUST have the user's Project URL and API Key. If not provided, ask the user first. Key distinction: Backend configuration uses HTTP API calls to the InsForge project URL. Client integration uses the @insforge/sdk in application code.
Bun as runtime, package manager, bundler, and test runner. When to choose Bun vs Node, migration notes, and Vercel support.
Skill for using Astro projects. Includes CLI commands, project structure, core config options, and adapters. Use this skill when the user needs to work with Astro or when the user mentions Astro.
This skill should be used when the user wants to list all projects, switch projects, rename a project, enable/disable PR deploys, make a project public/private, or modify project settings.
This skill should be used when the user wants to add a service from a template, find templates for a specific use case, or deploy tools like Ghost, Strapi, n8n, Minio, Uptime Kuma, etc. For databases (Postgres, Redis, MySQL, MongoDB), prefer the database skill.
Use when fine-tuning LLMs, training custom models, or optimizing model performance for specific tasks. Invoke for parameter-efficient methods, dataset preparation, or model adaptation.