Structured reasoning modifiers (/think, /verify, /adversarial, /edge, /confidence, /assumptions, etc.) to stress-test decisions, surface assumptions, or enumerate edge ca — from…
Use when when annotating large-scale untargeted metabolomics datasets where reference library coverage is incomplete and you need to infer metabolite identities for unannotated…
Extract the conceptual essence of a repository as skills, agents, and teams — the project's roles, procedures, and coordination patterns expressed as agentskills.io-standard…
Use when the user asks to add a connector, create a connector, implement a connector for a service, add a tool to a connector, update a connector tool, or asks about connector…
Expert guidance for micro — asynchronous HTTP microservices framework by Vercel. Use when building lightweight HTTP servers, API endpoints, or microservices using the mic — from…
Embedded firmware development for microcontrollers including memory-mapped I/O, GPIO, interrupts, timers, UART/SPI/I2C serial protocols, PWM generation, ADC sampling,…
Expert guidance for Micronaut framework development with compile-time dependency injection, GraalVM native builds, and cloud-native microservices
Guidelines for building production-grade microservices with FastAPI/Python and Go, covering serverless patterns, clean architecture, observability, and resilience.
Customize generated microservices.sh apps safely. Use inside a generated app when changing config, hooks, overlays, routes, UI, content, schemas, admin screens, smoke checks, or…
Plan new microservices.sh applications. Use when a user wants to build an app, choose a template, select modules, compare starters, scope an MVP, or turn a product idea into a…
Designs distributed system architectures, decomposes monoliths into bounded-context services, recommends communication patterns, and produces service boundary diagrams an — from…
Distributed systems expert specializing in service decomposition, orchestration, and microservices architecture patterns.
Microservices architecture patterns and best practices. Use when designing distributed systems, breaking down monoliths, or implementing service communication.
A Platform Architect interviewer testing your ability to decouple monoliths into microservices. Use this agent when you want to practice Domain-Driven Design (DDD), defining…
Create or update microservices.sh modules and templates. Use when authoring module.json, microservices.template.json, schemas, migrations, hooks, events, permissions,…
Split services along business capabilities with clear data ownership, avoiding the distributed monolith.
Plan and perform local-first data migrations into microservices.sh apps. Use for moving data from Supabase, Firebase, Postgres/Prisma, SQL dumps, CSV exports, legacy APIs, auth…
Decomposing a Rails monolith into services — bounded contexts, service boundaries, public-API contracts, ownership of data, service-to-service authentication, the "shared library"…
Microservices design patterns including service mesh, event-driven architecture, saga pattern, and API gateway
Conception et découpage d'architecture microservices. À utiliser pour concevoir ou migrer vers des microservices.
Master microservices architecture patterns including service boundaries, inter-service communication, data management, and resilience patterns for building distributed systems.
Design microservices architectures with service boundaries, event-driven communication, and resilience patterns.
Audit a microservices.sh app before pilot, client handoff, preview, or production. Use for launch readiness, security review, tenant isolation review, auth/payment/email/webhook…
Plan and configure external provider integrations in microservices.sh apps. Use for Stripe/payment, subscriptions, email providers, webhook delivery, Google Calendar, R2…
Help users build, inspect, customize, and deploy applications created with microservices.sh. Use when working in a generated microservices.sh app, choosing templates or modules,…
Microsoft Fabric workspace management, governance, REST API patterns, and medallion architecture implementation
Architectural patterns for org migration — org merge (consolidate two orgs into one), org split (separate one org into two), and coexistence (run both for a transition period with…
Migration orchestrator for aim/ → vehicle/ architecture migration. Use when porting functionality from the legacy monolithic AI stack to the new containerized vehicle platform.
Navigate Mind Palace to query entity knowledge about codebase subsystems. Use when understanding architecture, exploring how systems work, or checking for hazards/gotchas before…
Reference Architecture for MindTickle. Trigger: "mindtickle reference architecture".
Use when creating, redesigning, or maintaining an architecture, roadmap, implementation map, or system overview board in Miro.
Implement a production-ready reference architecture for Miro REST API v2 integrations with layered design, caching, and event processing.
Helps users run multiple concurrent mirrord sessions from a single mirrord-up.yaml (compose-style multi-service local debugging).
Use when designing the exhibits for a MIS Quarterly manuscript — measurement/correlation and structural-model tables for behavioral IS, regression and robustness tables for…
Ask questions against Mission Control's codebase understanding. Use for architecture questions, where-is-this-handled, why-does-this-exist, and codebase Q&A grounded in the…
Use when designing space missions, computing launch windows, optimizing trajectories, analyzing payload constraints, or planning mission phases and contingencies.
Implement Mistral AI reference architecture with best-practice project layout. Use when designing new Mistral AI integrations, reviewing project structure, or establishing…
Run a Mixture of Experts (MoE) audit on any topic, plan, codebase, evidence archive, or process. Dynamically spawns specialized subagents with different critical lenses to…
Deep expertise in ML/CV model selection, training pipelines, and inference architecture. Use when designing machine learning systems, computer vision pipelines, or AI-powered…
Use when the user wants an implementation plan, architecture design, or multi-step ML pipeline — "build X", "implement X", "design X", "set up X
Coaches end-to-end ML system design interviews covering inference pipelines, recommendation systems, RAG, feature stores, and monitoring.
A Principal ML Engineer interviewer that simulates a FAANG-style ML system design interview covering the full lifecycle from data to production.
Guides and validates architecture-aware ports of PyTorch/Hugging Face models to Apple MLX, inspects existing local MLX projects, and plans evidence-gated optimizations for Apple…
Alfred SuperAgent의 필수 규칙을 정의합니다. November 2025 enterprise standard 기반. 3-Layer architecture, 4-Step workflow, Agent-first paradigm, Skill invocation rules, AskUserQuestio — from…
Alfred SuperAgent의 필수 규칙을 정의합니다. November 2025 enterprise standard 기반. 3-Layer architecture, 4-Step workflow, Agent-first paradigm, Skill invocation rules, AskUserQuestio — from…
Authoring CLAUDE.md Project Instructions. Design project-specific AI guidance, document workflows, define architecture patterns.
Strategic thinking framework integrating First Principles Analysis, Stanford Design Thinking, and MIT Systems Engineering for deeper problem-solving.
Electron 33+ desktop app development specialist covering Main/Renderer process architecture, IPC communication, auto-update, and packaging with Electron Forge.
Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral).
State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design.
Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy.
RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential).
Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP).
Use when after a deep neural network model has completed training on LC-MS spectral peak classification data and you need to preserve the learned weights and architecture for…
Esposter model-delegation conventions — the main session does all thinking (specs, proposals, architecture, review); mechanical implementation is delegated to background subagents…
Use when you have a trained baseline GNN model with established hyperparameters (dropout rate, learning rate, epochs, optimizer settings) and want to evaluate whether alternative…
Shape source-backed model and diagram review artifacts for architecture, UML-style, C4, dependency, and workflow views.
Use when architecture boundaries, integrations, ownership, containers, components, deployment, dependencies, or stakeholder communication need C4-style views tied to value…
Skill para diseñar, revisar y generar artefactos de arquitectura modular (capas, features, boundaries, paquetes, y estrategias de integración).
Practical guidance for Go package design with minimal public APIs, single-responsibility boundaries, stateless-first flow, one-way state transitions, and…