Checks test isolation (API/DB/FS/Time/Network), determinism, flaky tests, order-dependency, anti-patterns. Use when auditing test isolation.
Checks manual test scripts for harness adoption, golden files, fail-fast, config sourcing, idempotency. Use when auditing manual test quality.
Checks test file organization, directory layout, test-to-source mapping, domain grouping, co-location. Use when auditing test structure.
Audits assertion strength and test oracles that prove real defects. Use when finding weak tests that execute code but prove little.
Checks layer boundary violations, transaction boundaries, session ownership, cross-layer consistency. Use when auditing architecture layers. — from engineering/architecture
Checks layer boundary violations, transaction boundaries, session ownership, cross-layer consistency. Use when auditing architecture layers. — from majiayu000/claude-skill-registry
Checks layer, resource ownership, and orchestration boundaries. Use when auditing architecture boundary enforcement.
Builds dependency topology, detects cycles, validates import rules, and calculates coupling metrics. Use when auditing architecture topology.
Finds architecture-level modernization opportunities: obsolete custom mechanisms, overbuilt extension points, and simplifiable architecture.
Audits architecture config boundaries: typed settings, scattered env reads, config leakage, and layer ownership. Use for config architecture.
Checks redundant fetches, N+1 loops, over-fetching, missing bulk operations, wrong caching scope. Use when auditing query efficiency.
Scaffolds new or restructures existing projects to Clean Architecture. Use when setting up project structure.
Scaffolds new React projects or restructures monoliths to component-based architecture. Use when setting up frontend structure.
Removes platform-specific artifacts from Replit, StackBlitz, CodeSandbox, Glitch. Use when preparing exported projects for production.
Sets up Docker, CI/CD, and environment configuration with auto-detection. Use when adding DevOps infrastructure to a project.
Sets up test infrastructure with Vitest, xUnit, and pytest. Use when adding testing frameworks and sample tests to a project.
Configures structured JSON logging with Serilog (.NET) or structlog (Python). Use when adding logging to backend projects.
Configures global exception handling middleware. Use when adding centralized error handling to .NET or Python backends.
Configures health check endpoints for Kubernetes readiness/liveness/startup probes. Use when deploying to Kubernetes.
Executes all test suites and reports results with coverage. Use when verifying that test infrastructure works after bootstrap.
Builds and launches Docker containers with health verification. Use when validating that containerized services start correctly.
Executes optimization hypotheses with keep/discard testing loop. Use when applying validated performance improvements.
Upgrades Python pip/poetry/pipenv dependencies with breaking change handling. Use when updating Python dependencies.
Replaces custom modules with OSS packages using atomic keep/discard testing. Use when migrating custom code to established libraries.
Disposable Lightning wallets via lncurl.lol. Use for temporary wallets, testing, or bootstrapping child agents.
Load architecture principles and core conventions for grounding work against project standards - simple context loading for all workflow stages
Helps write CUDA and HIP kernels using torch.utils.cpp_extension.load_inline(). Use when users want to write native GPU code (CUDA/HIP) inside a Python submission file.
Design a defensible load test — a realistic workload model, a deliberate test type, and SLO-tied pass/fail thresholds — instead of a meaningless tight-loop script that hammers one…
This ASE skill uses ghz to run repeatable gRPC load tests from proto files, protosets, or server reflection.
Planifie et exécute des tests de charge et performance. Se déclenche avec "test de charge", "load test", "stress test", "performance test", "k6", "JMeter", "Gatling", "be — from…
Creates comprehensive load test plans with realistic scenarios, traffic models, k6 scripts, and success criteria.
Load Test Scenario Planner - Auto-activating skill for Performance Testing. Triggers on: load test scenario planner, load test scenario planner Part of the Performance Testing…
Tester les performances sous charge. Utiliser quand on mesure la capacité du système ou optimise les temps de réponse.
Run load tests and profile applications with Locust, py-spy, and database query analysis
Execute comprehensive load and stress testing to validate API performance and scalability. Use when validating API performance under load.
k6 script templates, load profiles, response time thresholds, SLO validation, and performance testing strategies.
Write a load and performance testing plan for a service. Use when asked to create a performance test plan, write load testing documentation, define stress or soak test sc — from…
부하 테스트 자동화 하네스(loadtest-harness)를 end-to-end 실행한다 — 사전 점검 → run.py 실행(시나리오·회차 선택) → 생성된 리포트 요약까지. 사용자가 "부하 테스트 돌려줘", "하네스 실행", "knee-point 테스트 실행", "loadtest 돌려" 등을 요청할 때 사용.
Review the current session for durable learnings, then route each one through the five-way matrix: wiki page, guidance file, checkpoint, task annotation/plan, or discard.
Answer questions against existing memory (the wiki substrate). Use this whenever the user is asking what is happening in the project, directory, codebase, architecture, workflow,…
LobeChat - Open-source AI agent workspace with multi-provider LLM support, plugin system, knowledge base RAG, 505+ agents, and self-hosting options via Docker/Vercel
LobeTTS - High-quality TypeScript TTS/STT toolkit with EdgeSpeech, Microsoft, OpenAI engines, React hooks, audio visualization components, and both server and browser support
LobeHub is an open-source multi-agent chat platform supporting 50+ LLM providers, MCP plugin marketplace, knowledge base management, and multi-agent collaboration.
Software Development for Dummies: Guides no brainers through the software development process, providing step-by-step instructions and best practices for requirements gathering,…
LobsterTv is an AI agent live streaming platform. Agents connect via REST API to broadcast in real-time with rendered avatars, synchronized TTS audio, expression control, chat…
Remind the user to rebuild OMC after editing TypeScript when running from a local fork. Triggered automatically by the AI whenever it notices it (or the user) just changed a…
Run the same lint + typecheck + architecture-audit checks CI runs, locally and in parallel. Catches workspace-package issues (missing deps, prop drift, lint rule violations)…
remote CI (GitHub Actions) 相当のチェックをローカルで実行。Biome check、テスト、ビルドを並列実行し、全てのチェックが成功したことを確認する。PR作成前の事前チェックに使用。 — from majiayu000/claude-skill-registry-data
remote CI (GitHub Actions) 相当のチェックをローカルで実行。Biome check、テスト、ビルドを並列実行し、全てのチェックが成功したことを確認する。PR作成前の事前チェックに使用。 — from engineering/engineering-misc
Launch and manage OpenAI Codex CLI (local agent) as a non-interactive coding sub-agent. Use when the user wants to delegate coding tasks to Codex, run code reviews, generate or…
Build, stamp, and (re)launch threadbase-streamer locally on macOS, Linux, or Windows. Detects the OS and dispatches to the right deploy script (launchd / systemd-user / Task…
Как поднять локальный стенд Sb0rka (docker-compose: Postgres, auth, api, drones, proxy) и получить access-токен через auth (регистрация + логин).
Local LeadAce E2E testing skill. Triggers: 'local E2E', 'ローカル E2E', 'local-e2e', 'E2E テスト', E2E run against the local stack.
Local-First Sync Engine & Reactive Collection Architecture (ElectricSQL / TanStack DB style, query-driven sync, optimistic mutations with transactional rollback) for all coding…
Local Frappe development environment for testing APIs before production deployment. Use when developing or testing Python/API changes locally.
Leverage personal notes and documentation through Terraphim's role-based search. AI agents can search developer's local knowledge organized by domain (Rust, frontend,…
Manage local Ollama LLM models for development and testing. Use when: running local models, configuring Ollama, switching between fast/quality models, optimizing VRAM usage,…
Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio.
Use Clipboard's internal CLI to link and unlink @clipboard-health packages across repositories for local development.
Expert guide for understanding the Local Skills MCP server repository - its structure, architecture, and implementation.