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Found 412 Skills
Builds and deploys Docker containers on Render—Dockerfiles, multi-stage builds, Blueprint Docker fields, private registries, layer caching, and platform constraints. Use when the user mentions Docker, Dockerfile, container images, multi-stage builds, container registry, GHCR, ECR, BuildKit, dockerContext, runtime docker or image, or optimizing Docker builds on Render.
Execute web cache deception attacks by exploiting path normalization discrepancies between CDN caching layers and origin servers to cache and retrieve sensitive authenticated content.
Guide for configuring the Infisical Agent — a client daemon that manages token lifecycle and renders secrets via Go templates without modifying application code. Covers the full YAML config format, all 6 auth methods (Universal Auth, Kubernetes, AWS IAM, Azure, GCP ID Token, GCP IAM), sinks, template functions (listSecrets, listSecretsByProjectSlug, getSecretByName, dynamicSecret), polling, on-change commands, and caching. Use this skill when someone asks about: Infisical Agent, agent config file, agent templates, rendering secrets to files, sidecar secret injection, token renewal, infisical agent command, or 'how do I use the Infisical Agent to inject secrets'.
Build LLM-powered chat apps with the right SDK — Anthropic SDK / Claude API (prompt caching, thinking, tool use, batch, files, citations, memory, model migrations) AND Vercel AI SDK (useChat, streamText, tool calls, UIMessage, ChatStatus, addToolOutput). Use when implementing chat interfaces, tuning Claude features, migrating between Claude model versions, or wiring up streaming with @ai-sdk/react.
C# scripting in Unity for gameplay, behavior, and engine integration. PROACTIVELY activate for: (1) writing Unity C# scripts, (2) MonoBehaviour lifecycle (Awake/OnEnable/Start/Update/FixedUpdate/LateUpdate), (3) coroutines and async/await in Unity, (4) delegates, events, Action/Func patterns, (5) ScriptableObject creation and serialization, (6) GetComponent / TryGetComponent and component caching, (7) physics scripting (Rigidbody, raycast, collision/trigger callbacks), (8) animation scripting (Animator parameters, state machines, IK), (9) NavMesh and NavMeshAgent scripting, (10) input handling (Input System package), (11) custom serialization and SerializeField. Provides: lifecycle reference, coroutine vs async patterns, ScriptableObject templates, Rigidbody/collision recipes, NavMesh examples, and Input System setup.
Debug Next.js issues systematically. Use when encountering SSR errors, hydration mismatches like "Text content did not match", routing issues with App Router or Pages Router, build failures, dynamic import problems, API route errors, middleware issues, caching and revalidation problems, or performance bottlenecks. Covers both Pages Router and App Router architectures.
Debug Vue.js 3 application issues systematically. This skill helps diagnose and resolve Vue-specific problems including reactivity failures with ref/reactive, component update issues, Pinia store state management problems, computed property caching bugs, Teleport/Suspense rendering issues, and SSR hydration mismatches. Provides Vue DevTools usage, console debugging techniques, Vite dev server troubleshooting, and vue-tsc type checking guidance.
Connection pooling and caching for PostgreSQL and MySQL databases. Load when connecting Workers to existing Postgres/MySQL, reducing connection overhead, using Drizzle/Prisma with external databases, or migrating traditional database apps to the edge.
Backend API design, database architecture, microservices patterns, and test-driven development. Use for designing APIs, database schemas, or backend system architecture.
Diagnose, fix, and optimize GitHub Actions workflows for Rust projects. Use when setting up CI/CD, troubleshooting workflow failures, optimizing build times, or ensuring best practices.
AI session compression techniques for managing multi-turn conversations efficiently through summarization, embedding-based retrieval, and intelligent context management.
HyDE (Hypothetical Document Embeddings) for improved semantic retrieval. Use when queries don't match document vocabulary, retrieval quality is poor, or implementing advanced RAG patterns.