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Found 1,248 Skills
Build Grafana plugin pages using the @grafana/scenes framework. Use this skill when creating new scene pages, adding panels/visualizations, setting up drilldown navigation, defining variables, configuring query runners, building table/timeseries/stat panels, or extending SceneObjectBase for custom scene objects. Triggers on any work involving SceneApp, SceneAppPage, EmbeddedScene, SceneQueryRunner, SceneDataTransformer, PanelBuilders, SceneFlexLayout, QueryVariable, or drilldown/tab configuration in Grafana plugins.
Software Mansion's guide for migrating Expo SDK apps to Meta Quest using expo-horizon packages. Use when adding Meta Quest or Meta Horizon OS support to an existing Expo or React Native project. Trigger on: Meta Quest, Horizon OS, Quest 2, Quest 3, Quest 3S, VR app, expo-horizon-core, expo-horizon-location, expo-horizon-notifications, build flavors for Quest, panel sizing, VR headtracking, Horizon App ID, quest build variant, isHorizonDevice, isHorizonBuild, migrate expo-location to Quest, migrate expo-notifications to Quest, Meta Horizon Store publishing, or any task involving running an Expo app on Meta Quest hardware.
Automates declarative resource creation and provisioning for data pipelines, supporting BigQuery, Dataform, Dataproc, BigQuery Data Transfer Service (DTS), and other resources. It manages environment-specific configurations (dev, staging, prod) through a deployment.yaml file. Use when: - Modifying or creating deployment.yaml for deployment settings. - Resolving environment-specific variables (e.g., Project IDs, Regions) for deployment. - Provisioning supported infrastructure like BigQuery datasets/tables, Dataform resources, or DTS resources via deployment.yaml. Do not use when: - Resources already exist. - Managing resources not supported by `gcloud beta orchestration-pipelines resource-types list`. - Managing general cloud infrastructure (VMs, networks, Kubernetes, IAM policies), which are better suited for Terraform. - Infrastructure spans multiple cloud providers (AWS, Azure, etc.). - Already uses Terraform for the target resources.
Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.
Generates high-converting landing pages as complete Next.js/React (TSX) components with Tailwind CSS. Creates hero sections, feature grids, pricing tables, FAQ accordions, testimonial blocks, and CTA sections using proven copy frameworks (PAS, AIDA, BAB). Outputs SEO meta tags, structured data, and performance-optimised code targeting Core Web Vitals (LCP < 1s, CLS < 0.1). Use when the user asks to create a landing page, marketing page, homepage, single-page site, lead capture page, campaign page, promo page, or conversion-optimised web page — or when they want to A/B test landing page variants or replace a static page with one designed to convert.
Validate domain boundaries -- detect cross-context import violations and aggregate invariant issues
Evaluate Omni AI query generation accuracy by running test prompts through the Omni CLI, comparing generated query JSON against expected results, and scoring accuracy. Use this skill whenever someone wants to evaluate Omni AI, benchmark Blobby, run regression tests, compare AI output across branches or configurations, test prompt variations, measure AI quality, run A/B tests on model changes, assess impact of context changes, or any variant of "run evals", "test Blobby", "benchmark query generation", "compare AI results", "regression test", "how accurate is the AI", or "measure the impact of my changes".
Manages Medusa Cloud resources through the Cloud CLI (mcloud). Use when deploying, debugging deployments, managing environments, environment variables, or any Medusa Cloud operation. CRITICAL for mcloud commands, deployment failures, build logs, Cloud setup, and CI/CD workflows.
Async media + document derivations via `platform.media.transforms` and the declarative `transforms` block in `maravilla.config.ts`. Media: transcode video, thumbnail extraction, image resize/variants, OCR. Documents (.docx/.odt/.pptx/.xlsx/...): convert to PDF, render page thumbnails, generic format conversion, Markdown extraction (RAG-ready), single-file HTML with inlined images, image-replacement templating ({{TAG}} swap + named-object swap), QR-code injection. Use when ingesting user uploads that need normalised renditions, generating contracts/invoices from templates, or extracting structured content for LLMs. Critical: derived keys are content-addressed — `keyFor(srcKey, spec)` is known up front, before the worker starts, so clients can render placeholder UI without round-trips. Declarative config is the default; imperative `transforms.*` calls are for one-offs.
Use when writing, fixing, or editing TypeScript code that touches APIs, JSON, environment variables, storage, databases, browser APIs, SDKs, generated clients, or other external boundaries.
Use when the user wants to author, refine, or audit a Product Requirements Document for AI coding agents. Walks through an 8-phase pipeline (Socratic discovery → PRD draft → acceptance criteria → adversarial review → task decomposition → AI-readiness gate → test generation → handoff). Triggers on "write a PRD", "spec this feature", "draft requirements", "prepare X for Claude/Cursor/Copilot/Windsurf/Aider to build", "audit my PRD", "is this PRD AI-ready", "score this spec".
Run Figma Plugin API scripts for canvas writes, inspections, variables, and design-system work. Prerequisite for every other Figma skill in this catalogue.