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Found 2,347 Skills
Design end-of-article CTAs (calls-to-action placed at the bottom of blog posts, newsletters, essays, articles, or any long-form content). Use this skill whenever the user asks to write, design, review, or improve a CTA at the bottom of an article, blog post, or essay; mentions "end-of-post CTA", "bottom of the article", "call-to-action", "signup box", "newsletter CTA", "subscribe block", "what should I put at the bottom", "how do I get readers to subscribe / share / book a call / buy / follow / join / download"; or asks how to convert article readers into subscribers, leads, customers, community members, or supporters. Also trigger when the user wants A/B testing guidance or accessibility review for a CTA block. Covers independent / personal writing, newsletter publications, and brand / content-marketing blogs across any topic — tech, finance, food, climate, design, lifestyle, B2B, B2C. Produces both the copy (content) and the structural / visual design (form), matched to the user's objective and audience.
Develop and deploy Data Cloud Code Extensions using SF CLI plugin. Use this skill when creating custom Python transformations for Data Cloud, deploying code extensions, or testing data transformations. Supports init, run, scan, and deploy operations.
Configures DevOps Center pipeline testing infrastructure: enables a test provider so its suites become available, re-syncs a configured provider to pull in new suites, or creates a quality gate with rules on a stage. Routes by intent across three modes after running shared prerequisite checks and an explicit confirmation gate. Use this skill when a user wants to set up, configure, enable, sync, or refresh a test provider, or set/configure a quality gate or coverage threshold on a DevOps Center pipeline stage. TRIGGER when: the user wants to configure/enable/add/set up a test provider, re-sync or refresh a provider's suite list, pull in new suites, or set/configure a quality gate, coverage threshold, or testing benchmark on a stage. DO NOT TRIGGER when: assigning existing suites to a stage (use dx-devops-test-suite-assignments-configure), running or retriggering a suite (use dx-devops-test-suite-run), or non-DevOps-Center work.
Use when someone asks to generate ad copy, write headlines, create copy suggestions, or draft marketing text — without generating a design. Also use when the user mentions 'copy suggestions,' 'headline ideas,' 'ad copy,' 'write copy for my ad,' 'content for my design,' 'text for my banner,' 'offer text,' 'bullet points for my ad,' 'CTA text,' or 'what should my ad say.' Generates structured copy variations using content expert instructions — no API call needed. Default is 2 variations; user can request more (e.g., 3–4 for A/B testing). Copy is presented in readable format for user review and edit, with JSON output for use in generate-design. For generating designs (which now includes copy generation as step 1), see generate-design.
Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail). Covers ASL syntax, JSONata data transformation and variables, Retry/Catch error handling, service integrations (.sync, waitForTaskToken callbacks), Distributed Map for large-scale S3/CSV processing, saga/compensation patterns, Standard vs Express workflow choice, TestState API unit testing, and migrating state machines from JSONPath to JSONata. Use when the user is building, authoring, debugging, or migrating a Step Functions state machine or ASL definition, or orchestrating multi-step workflows with branching, retries, or human-approval callbacks, even if they don't say 'Step Functions.' Do NOT use for general Lambda function code, API Gateway, EventBridge wiring, or SAM/CDK application packaging.
Facilitates the second step of a proven customer-interview method: recording the user's current best guesses — hypotheses — as numbered, falsifiable statements (H1, H2, …), each mapped to the goal questions it addresses, so interviews can confirm or contradict them instead of confirmation bias quietly filtering what's heard. Takes a GOALS.md goal-question list as input (file or pasted), elicits what the user believes goal by goal, sharpens vague beliefs into testable claims, prunes to hypotheses whose resolution would actually change what the user builds, targets, charges, or says, and preserves the result in HYPOTHESES.md. Load when the user has goal questions and wants to write hypotheses, list their assumptions, or record predictions before interviewing customers — 'I have my goals, what's next,' 'help me write down what I believe about my customers.' Do NOT load for writing the interview questions themselves, for analyzing interviews already conducted, or for statistical hypothesis testing.
One page, hands-on manual tier — drive a live page through the web accessibility (a11y) checks a rule engine can't decide: keyboard operation and focus order, screen-reader names, roles and states from the accessibility tree, reflow and zoom, reduced motion, form errors, and target size. Grades each finding by evidence basis (verified / confirm-with-a-human / human-required) and severity, and closes every criterion in a ledger: verified, flagged, not exercised, or N/A. Locates and assesses; does not fix (use `accessibility-fix`). Use it for keyboard testing, focus-order checks, screen-reader or a11y-tree review, reflow and zoom at 200%, or 'is this operable, not just lint-clean'. The automated tier is `accessibility-scan`; `accessibility-audit` runs both across a sampled site.
Use when installing or running the Inngest CLI and Dev Server for local development, local testing, serve endpoint debugging, Docker or Docker Compose setup, MCP configuration, self-hosted `inngest start`, or deployment workflow checks. Covers `inngest dev`, `inngest start`, auto-discovery, config files, environment variables, `@inngest/test`, local event sending, platform gotchas, and production/self-hosted server flags.
Test payment and checkout flows end to end against PSP sandboxes — Stripe first, with the general pattern for Adyen/Braintree/PayPal. Covers Stripe test-mode card numbers and their decline codes, the 3DS/SCA challenge flow and its nested-iframe handling in Playwright, test clocks for subscription/billing-cycle simulation, webhook testing (stripe listen/trigger, signature verification, idempotency), failed/retried payments and refunds, and never using real cards. Use when: "test Stripe checkout," "payment test," "3DS test," "test webhook signature," "test subscription renewal," "test clock," "refund test," "decline card test," "checkout E2E." Not for: General API contract testing of non-payment endpoints — api-testing. PCI-DSS/regulatory compliance audit — compliance-testing. Related: api-testing, playwright-automation, compliance-testing, test-data-management, qa-project-context.
Use for authorized security assessment of REST, GraphQL, WebSocket, or SOAP APIs, including discovery, authentication, authorization, rate-limit, and CI/CD testing.
Advanced and operational chat.agent capabilities for Trigger.dev, loaded on demand. Load this when working on the raw Sessions primitive (sessions / SessionHandle), a custom chat transport or the realtime wire protocol, durable sub-agents (AgentChat, chat.stream.writer), human-in-the-loop, steering, actions, background injection (chat.defer / chat.inject), fast starts (preload, Head Start via @trigger.dev/sdk/chat-server), context resilience (compaction, recovery boot, OOM, large payloads), chat.local run-scoped state, offline testing with mockChatAgent, or prerelease/version upgrades. For the everyday chat.agent({...}) definition and the useTriggerChatTransport happy path, use the trigger-authoring-chat-agent skill instead.
Build, scaffold, refactor, debug, review, and visually validate production Rust desktop interfaces with GPUI. Use for setting up a production-ready GPUI starter app; new GPUI apps or components; Entity, Context, action, async, and lifecycle architecture; Apple-style macOS UI, Liquid Glass or translucent materials, motion, gestures, focus, keyboard, accessibility, text input, IME, clipboard, drag and drop, menus, multi-window behavior, and restoration; packaging, CI, performance, and testing work; or translating selected Paper.design frames into maintainable GPUI code with screenshot comparison. Covers published GPUI and pinned Zed revisions, macOS/Linux/Windows boundaries, narrow AppKit interop, and stability audits.