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Found 1,282 Skills
Amazon Bedrock AgentCore Policy for defining agent boundaries using natural language and Cedar. Deterministic policy enforcement at the Gateway level. Use when setting agent guardrails, access control, tool permissions, or compliance rules.
TypeScript-first schema validation and type inference. Use for validating API requests/responses, form data, env vars, configs, defining type-safe schemas with runtime validation, transforming data, generating JSON Schema for OpenAPI/AI, or encountering missing validation errors, type inference issues, validation error handling problems. Zero dependencies (2kb gzipped).
This skill should be used when users need to interact with Kubernetes clusters via kubectl CLI. It covers pod management, deployment operations, log viewing, debugging, resource monitoring, scaling, ConfigMaps, Secrets, Services, and all standard kubectl operations. Supports multiple clusters (production, staging, local k3s) with predefined aliases. Triggers on requests mentioning Kubernetes, k8s, pods, deployments, containers, or cluster operations.
Use when a TypeScript/JavaScript task needs symbol navigation (`nav declarations|definition|references`), structural pattern search (`search`), structural rewrites (`patch`), or reference-based blast-radius estimation (`code-rank`). Prefer for compact, scoped repository analysis and migration work; do not use for runtime-path proofs, correctness guarantees, or replacing compiler/tests.
Define or refresh a product North Star metric + driver tree and produce a shareable North Star Metric Pack (narrative, metric spec, inputs, guardrails, rollout).
gRPC and Protocol Buffers - use for service-to-service communication, API definitions, streaming, and inter-service contracts
Scala resource lifecycle management with Cats Effect `Resource` and `IO`. Use when defining safe acquisition/release, composing resources (including parallel acquisition), or designing resource-safe APIs and cancellation behavior for files, streams, pools, clients, and background fibers.
AWS ECS container orchestration for running Docker containers. Use when deploying containerized applications, configuring task definitions, setting up services, managing clusters, or troubleshooting container issues.
Defines right metrics using North Star framework, AARRR, and leading vs lagging indicators. Use when choosing metrics, instrumenting products, creating dashboards, or distinguishing vanity metrics from actionable ones.
Crafts product positioning using April Dunford's positioning framework. Use when defining target customers, choosing categories, identifying alternatives, or articulating differentiated value. Based on Obviously Awesome methodology.
Complete knowledge domain for Cloudflare Browser Rendering - Headless Chrome automation with Puppeteer and Playwright on Cloudflare Workers for screenshots, PDFs, web scraping, and browser automation workflows. Use when: taking screenshots, generating PDFs from HTML or URLs, web scraping content, crawling websites, browser automation tasks, testing web applications, managing browser sessions, performing batch browser operations, integrating with AI for content extraction, or encountering browser rendering errors, XPath selector errors, browser timeout issues, concurrency limits, memory exceeded errors, or "Cannot read properties of undefined (reading 'fetch')" errors. Keywords: browser rendering cloudflare, @cloudflare/puppeteer, @cloudflare/playwright, puppeteer workers, playwright workers, screenshot cloudflare, pdf generation workers, web scraping cloudflare, headless chrome workers, browser automation, puppeteer.launch, playwright.chromium.launch, browser binding, session management, puppeteer.sessions, puppeteer.connect, browser.close, browser.disconnect, XPath not supported, browser timeout, concurrency limit, keep_alive, page.screenshot, page.pdf, page.goto, page.evaluate, incognito context, session reuse, batch scraping, crawling websites
Expert guidance for working with Dagster and the dg CLI. ALWAYS use before doing any task that requires knowledge specific to Dagster, or that references assets, materialization, or data pipelines. Common tasks may include creating a new project, adding new definitions, understanding the current project structure, answering general questions about the codebase (finding asset, schedule, sensor, component or job definitions), debugging issues, or providing deep information about a specific Dagster concept.