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Found 7,945 Skills
Use when making design decisions, implementing HIG patterns, Liquid Glass, SF Symbols, typography, or structuring app entry points and authentication flows.
Generate comprehensive test plans, test cases, regression test suites, automation annotations, and bug reports for QA engineers. Includes Figma MCP integration for design validation. Use when planning QA before execution, documenting test strategies, marking which flows require E2E follow-up, or creating structured bug reports. Do not use for executing tests against a live repository or running verification gates — use qa-execution for that.
Executes full-project QA like a real user by discovering the repository verification and E2E contracts, running build, lint, test, and startup commands, exercising core workflows end-to-end through CLI, HTTP, and browser interfaces, requiring automated regression coverage for supported critical flows, fixing root-cause regressions, and rerunning the full gate. Uses the agent-browser companion skill for Web UI validation when a web surface exists. Use when validating a branch, release candidate, migration, refactor, or risky commit. Do not use for static code review only, one-off unit test edits, planning test cases, or architecture brainstorming without execution — use qa-report for planning and documentation.
Grafana Alerting, Incident Response Management (IRM), and SLOs. Covers Grafana-managed and data source-managed alert rules, notification policies, contact points (Slack/PagerDuty/email/webhook), silences, muting, on-call scheduling, incident management workflows, and SLO configuration with burn-rate alerts. Use when configuring alerts, debugging notification routing, setting up on-call rotations, managing incidents, defining SLOs, or provisioning alerting via YAML/API.
**Opt-in DSL path** for NocoBase app building. Use ONLY when the user explicitly asks for YAML / DSL / committed-to-git / `cli push` / spec files — e.g. "use the DSL reconciler", "I want YAML I can commit", "build this as a workspaces/ project". For any other UI authoring request (new page, new block, tweak an existing screen), default to `nocobase-ui-builder` instead — this reconciler is still in active development and has rough edges that the live-UI path avoids. When the user opts in: produces/changes files under `workspaces/<project>/`, supports new pages, menus, modules, whole systems, collections, tables, sub-tables, popups, dashboards, approval workflows, recordActions, and deploys them via `cli push`.
Write application code that integrates with third-party tools via the Truto unified API. Covers API calls, webhook handlers, connection flows, and data access patterns for use in the user's codebase.
Use this skill whenever the user wants browser-based end-to-end tests for an Adobe App Builder application. Covers Playwright E2E testing for ExC Shell SPAs, AEM extension UIs, and full-stack flows. Use when the user mentions: "E2E test", "end-to-end test", "Playwright", "browser test", "test my SPA in the browser", "test my AEM extension", "test the full flow", "integration test with UI", "headless browser test", "E2E in CI". This skill is for BROWSER-based testing only. For Jest unit tests of actions or React components, use appbuilder-testing instead.
Build, modify, debug, and deploy agents with Agentforce Agent Script. TRIGGER when: user creates, modifies, or asks about .agent files or aiAuthoringBundle metadata; changes agent behavior, responses, or conversation logic; designs agent topics, actions, tools, sub-agents, or flow control; writes or reviews an Agent Spec; previews, debugs, deploys, publishes, or tests agents; uses Agent Script CLI commands (sf agent generate/preview/publish/test). DO NOT TRIGGER when: Apex development, Flow building, Prompt Template authoring, Experience Cloud configuration, or general Salesforce CLI tasks unrelated to Agent Script.
Use when adding login, logout, and user profile to a Flask web application using session-based authentication - integrates auth0-server-python for server-rendered apps with login/callback/profile/logout flows.
Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines or running distributed hyperparameter sweeps.
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
cuTile Python DSL kernel implementation patterns, CtKernel runtime wrapper, suitability gate, and cuTile-specific pitfalls. Use when: (1) creating or modifying a cuTile Python DSL kernel version, (2) implementing an optimization that still fits within cuTile's exposed control surface, (3) deciding whether cuTile is still the right DSL, (4) reviewing cuTile-specific runtime patterns. Always also load /design-kernel for shared naming, versioning, and workflow.