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Found 2,451 Skills
Unified Dinachi skill for fast component integration and plan-first generative UI guidance. Use when users ask to initialize/add Dinachi components, build concrete UI features quickly, map ambiguous product requirements to Dinachi recipes, or validate generated UI plans before implementation.
Implements OpenTelemetry (OTEL) logging with trace context correlation and structured logging. Use when setting up production logging with OTEL exporters, structlog/loguru integration, trace context propagation, and comprehensive test patterns. Covers Python implementations for FastAPI, Kafka consumers, and background jobs. Includes OTLP, Jaeger, and console exporters.
Generates production-ready API clients with TypeScript types, retry logic, rate limiting, authentication (OAuth, API keys), error handling, and mock responses. Use when user says "integrate API", "API client", "connect to service", or requests third-party service integration.
Provides domain knowledge and guidance for the Flare Time Series Oracle (FTSO)—block-latency feeds, Scaling anchor feeds, feed IDs, onchain and offchain consumption, fee calculation, delegation, and smart contract integration. Use when working with FTSO, price feeds, oracle data, feed consumption, volatility incentives, or Flare Developer Hub FTSO guides and starter repos.
Stripe payment integration with Node.js SDK. Covers Checkout Sessions, Payment Intents, Subscriptions, Customer Portal, webhooks, and Stripe Elements. Use when implementing checkout flows, payment processing, subscription billing, webhook handlers, or payment forms with Stripe Elements. Use for stripe, payments, checkout, subscriptions, billing, webhooks, payment intents, stripe elements.
End-to-end ERP + tax intelligence engineer skill: SAP Business One functional parity, Odoo 18 CE/OCA-compliant implementation, and deep Finance Tax Pulse (PH tax) integration.
Manual QA testing — verify features end-to-end as a user would, using every tool available (browser, macOS, bash, APIs). Focuses on what formal test suites cannot capture: visual correctness, UX flows, usability judgment, integration reality, edge cases, and failure modes. Standalone or composable with /ship. Triggers: qa, qa test, manual test, test the feature, verify it works, exploratory testing, smoke test, end-to-end verification.
ConvexFS (convex-fs) — path-based file storage and serving component for Convex powered by bunny.net CDN. Covers installation, setup, file upload/download flows, path management, blob lifecycle, atomic transactions (move/copy/delete), compare-and-swap, signed URLs, file expiration, garbage collection, auth for uploads/downloads, multiple filesystems, React integration, and production best practices. Use when working with ConvexFS, uploading files in Convex, serving files via CDN, managing file paths, building file storage features, or configuring bunny.net with Convex. Triggers on: convex-fs, ConvexFS, bunny.net, file upload, file storage convex, blob, commitFiles, registerRoutes, buildDownloadUrl, fs.stat, fs.list, fs.transact, fs.move, fs.copy, fs.delete, fs.writeFile, fs.getDownloadUrl, "how do I upload files in Convex", "serve files from Convex", "ConvexFS setup".
Uniwind (Tailwind CSS v4 for React Native) best practices, setup, theming, styling, and HeroUI Native integration. Use when writing, reviewing, or fixing Uniwind code. Triggers on: uniwind, className on RN components, global.css with @import 'uniwind', withUniwindConfig, metro.config.js setup, dark:/light: theming, platform selectors (ios:/android:/native:/web:), data selectors, responsive breakpoints, CSS variables, useUniwind, withUniwind, useResolveClassNames, useCSSVariable, tailwind-variants, HeroUI Native with Uniwind, Uniwind Pro (animations, shadow tree, transitions), NativeWind migration. Also triggers on setup troubleshooting: "check my config", "styles not working", "className not applying", "audit Uniwind setup".
Master third-party API integration in ANY language with best practices and patterns
Integration templates for FastAPI endpoints, Next.js UI components, and Supabase schemas for ML model deployment. Use when deploying ML models, creating inference APIs, building ML prediction UIs, designing ML database schemas, integrating trained models with applications, or when user mentions FastAPI ML endpoints, prediction forms, model serving, ML API deployment, inference integration, or production ML deployment.
Summarize database schema design from requirement inputs and produce implementation-ready outputs for Go + Ent in this repository. Use when the input may be a prompt, Markdown requirement document, repository folder, or runnable demo behavior and you need entity extraction, field/constraint design, weak-relation ID strategy, index planning, Ent schema guidance, and concrete bind/render/service integration impacts.