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Found 2,505 Skills
C++ Reinforcement Learning best practices using libtorch (PyTorch C++ frontend) and modern C++17/20. Use when: - Implementing RL algorithms in C++ for performance-critical applications - Building production RL systems with libtorch - Creating replay buffers and experience storage - Optimizing RL training with GPU acceleration - Deploying RL models with ONNX Runtime
Security-first visual testing combining URL validation, PII detection, and visual regression with parallel viewport support. Use when testing web applications that handle sensitive data, need visual regression coverage, or require WCAG accessibility compliance.
Comprehensive code review with parallel specialist sub-agents. Analyzes requirements traceability, code quality, security, performance, accessibility, test coverage, and technical debt. Produces detailed findings and calls /qa-gate for final gate decision.
Implements Redis patterns for caching, sessions, rate limiting, pub/sub, and distributed locks with best practices. Use when users request "Redis caching", "session storage", "rate limiter", "pub/sub messaging", or "distributed locks".
Appwrite Python SDK skill. Use when building server-side Python applications with Appwrite, including Django, Flask, and FastAPI integrations. Covers user management, database/table CRUD, file storage, and functions via API keys.
Appwrite Dart SDK skill. Use when building Flutter apps (mobile, web, desktop) or server-side Dart applications with Appwrite. Covers client-side auth (email, OAuth), database queries, file uploads with native file handling, real-time subscriptions, and server-side admin via API keys for user management, database administration, storage, and functions.
Automate Supabase database queries, table management, project administration, storage, edge functions, and SQL execution via Rube MCP (Composio). Always search tools first for current schemas.
Complete Convex development mastery — functions (queries, mutations, actions, HTTP actions), schema design, index optimization, argument/return validation, authentication, security patterns, error handling, file storage, scheduling, crons, aggregates, OCC handling, denormalization, TypeScript best practices, and production-ready code organization. The definitive Convex skill. Use when building any Convex backend: writing functions, designing schemas, optimizing queries, handling auth, adding real-time features, setting up webhooks, scheduling jobs, managing file uploads, or reviewing/fixing Convex code. Triggers on: convex, query, mutation, action, ctx.db, defineSchema, defineTable, v.id, v.string, v.object, withIndex, ConvexError, internalMutation, httpAction, ctx.scheduler, ctx.storage, OCC, convex best practices, convex functions, convex schema, convex performance, "how do I do X in Convex".
Guide for writing tests. Use when adding new functionality, fixing bugs, or when tests are needed. Emphasizes integration tests, real-world fixtures, and regression coverage.
Comprehensive vitest testing patterns covering test structure, AAA pattern, parameterized tests, assertions, mocking, test doubles, error handling, async testing, and performance optimization. Use when writing, reviewing, or refactoring vitest tests, or when user mentions vitest, testing, TDD, test coverage, mocking, assertions, or test files (*.test.ts, *.spec.ts).
Comprehensive Kubernetes and OpenShift cluster management skill covering operations, troubleshooting, manifest generation, security, and GitOps. Use this skill when: (1) Cluster operations: upgrades, backups, node management, scaling, monitoring setup (2) Troubleshooting: pod failures, networking issues, storage problems, performance analysis (3) Creating manifests: Deployments, StatefulSets, Services, Ingress, NetworkPolicies, RBAC (4) Security: audits, Pod Security Standards, RBAC, secrets management, vulnerability scanning (5) GitOps: ArgoCD, Flux, Kustomize, Helm, CI/CD pipelines, progressive delivery (6) OpenShift-specific: SCCs, Routes, Operators, Builds, ImageStreams (7) Multi-cloud: AKS, EKS, GKE, ARO, ROSA operations
Create comprehensive unit tests, integration tests, and end-to-end tests using pytest for Python projects. Specializes in FastAPI testing with TestClient, async testing with pytest-asyncio, SQLModel/SQLAlchemy database testing, fixture generation, and test configuration setup. Use when you need test coverage, want to implement TDD/BDD, create test suites for functions or API endpoints, add edge case testing, or improve code quality with automated testing. Triggers include requests like "write tests for this module", "create pytest fixtures", "test this FastAPI endpoint", "setup pytest configuration", or "generate test file".