aiee-skills

Sprint planning patterns including effort estimation, cross-project validation, ticket refinement workflows, two-validator parallel intent-only refinement, Foundation→Gates ticket pairs, workstream split thresholds, and hub/per-project reconciliation. Use for sprint capacity planning, ticket validation, dependency discovery, tier-gated dispatch, strategic pivots, or coordinating multi-agent ticket processing.

Multimodal AI patterns for extracting structured information from video using Gemini, GPT-4o, and Claude vision. Frame sampling strategies, structured output with Pydantic, temporal reasoning, and cost optimization. Use for video analysis, report generation from video, and visual inspection.

Apple Foundation Models framework for on-device AI. LanguageModelSession, @Generable macro, structured output, token management, and availability checking.

Tactical DDD patterns for clean Python architecture including Domain Model, Repository, Service Layer, Unit of Work, and Aggregates. Use for backend architecture decisions, implementing data access layers, separating business logic from infrastructure, or reviewing code separation.

Architecture Decision Records (ADRs) for documenting significant technical decisions. Use for capturing decision context, rationale, consequences, and maintaining decision history.

Architecture visualization patterns using Mermaid and ASCII diagrams. Use for service flows, sequence diagrams, C4 models, decision matrices, or expressing architectural ideas visually.

Event-driven architecture patterns for Python including Domain Events, Commands, Message Bus, CQRS, and Bootstrap. Use for implementing event sourcing, decoupled workflows, reactive systems, microservices integration, or making decisions about event-driven design.

MVP definition, MoSCoW prioritization, and phased delivery planning. Use for scoping minimum viable products, ordering features by value and dependency, or creating implementation roadmaps.

Modern Python 3.10+ development standards including type hints, async patterns, pathlib, dataclasses, and recommended tooling (uv, Ruff, pytest). Use for Python code review, new feature implementation, refactoring legacy code, or making architecture decisions about Python projects.

AWS App Runner and ECS Express Mode deployment patterns for stateless Python services. Use when deploying containerized APIs, configuring health checks, managing auto-scaling, or migrating from App Runner to ECS Express Mode.

CI/CD patterns for AWS using GitHub Actions, ECR, and App Runner/ECS Express Mode. Use for deployment pipelines, container image management, OIDC authentication, or automating deployments to AWS services.

AWS security hardening patterns including IAM least privilege, GitHub OIDC federation, Secrets Manager, and container security. Use for securing AWS resources, eliminating long-lived credentials, IAM trust policy configuration, or implementing defense in depth.

Azure Functions Python v2 programming model patterns for Service Bus-triggered services. Covers function_app.py shape, host.json for Premium SKU + Service Bus extension v5, lazy-init startup-state pattern, DefaultAzureCredential reuse, identity-based connections, custom container deployment, and the Dynatrace Functions extension. Use when migrating a long-lived worker/consumer to Functions, building a new Functions Service Bus consumer, or assessing Functions feasibility for an existing async-Python codebase. Call for function_app.py, service_bus_queue_trigger, func.FunctionApp, host.json, azure functions python v2 programming model, dynatrace functions extension.

Azure AD machine-to-machine authentication for Python services using azure-identity (DefaultAzureCredential, ManagedIdentityCredential, ClientSecretCredential) and MSAL (ConfidentialClientApplication). Covers KeyVault secret access, token caching, Managed Identity vs Service Principal decision, and AKS Workload Identity. Use for service-to-service auth, KeyVault integration, and credential rotation in Azure-hosted Python microservices.

Azure Service Bus async producer/consumer patterns with azure-servicebus 7.x — singleton credential, AutoLockRenewer for long jobs, dead-letter queue routing, Pydantic event schemas per queue, state-machine idempotency. Use for queue-based microservices, document processing pipelines, or async workflows on Azure. See `arch-events` for event-driven concepts.

Time-bound reference for comparing Camunda, Azure Functions, Dapr, and KEDA as workflow execution models in Azure-native environments. Use when evaluating execution model candidates for a service orchestration layer, or when assessing claims about these technologies in architecture comparison artifacts. Call for Camunda Python SDK, Zeebe streaming, Dapr CNCF status, Azure Functions timeout, KEDA workload identity, or any freshness check on vendor-specific execution-model facts.

Caddy as a zero-config TLS reverse proxy for single-service EC2 deployments. Auto-provisioned Let's Encrypt certs, 3-line Caddyfile, systemd integration. Use when terminating HTTPS on EC2 for a Dockerized service, avoiding ALB costs, or replacing nginx+certbot.

Security and privacy compliance patterns for B2B SaaS. Use for SOC 2 audit preparation, GDPR compliance, audit logging, PII handling, data subject rights, or building compliance controls into features.

Human-in-loop design system workflow using AI generation (Gemini) for brand identity exploration, dual-format token output (CSS + Swift), and WCAG contrast validation. Use when establishing a brand identity for a new product, generating design tokens for web and iOS, or validating a color palette against WCAG contrast requirements.

Systematic production debugging patterns including hypothesis-driven investigation, temporal regression analysis, and environment-first triage. Use when diagnosing production failures, investigating regressions, or debugging issues without an obvious root cause. Call for recently broken features, hypothesis enumeration, or root cause analysis.

Development standards for Python projects including code style, git conventions, testing patterns, timing measurement, and validation requirements. Use when writing code, reviewing PRs, or making commits. Loaded by all implementation agents.

Multi-stage Docker builds for Poetry-based Python services. Specializes the Poetry export pattern, production uvicorn configuration, slim-bullseye base image choice, and BuildKit layer caching. Sibling skill to docker-python (which covers Python 3.12 / Trixie / OpenCV foundations). Use for production Dockerfiles for FastAPI/uvicorn services using Poetry as the dependency manager.

Docker patterns for Python 3.12+ applications. Debian Trixie breaking changes, OpenCV dependencies, setuptools compatibility, and port mapping verification. Use when building Dockerfiles for Python services.

Modern FastAPI 0.111+ production patterns for Python services — async lifespan, Pydantic v2 schemas, dependency injection, middleware ordering, structured exception handlers, router composition. Use for FastAPI endpoint design, service composition, API contract evolution, and migrating from `@app.on_event` / Pydantic v1.

FFmpeg integration with Laravel for video processing. Thumbnail generation, format conversion, video metadata extraction, streaming. Use for video upload features, thumbnail generation, or media processing.

Formik + Yup for React Native. TextInput integration, mobile validation UX, error timing. Use when building mobile forms with validation, handling keyboard/focus UX, or wiring Yup schemas to Formik in RN.

Web accessibility patterns for WCAG 2.1 AA compliance including ARIA, keyboard navigation, screen reader support, contrast ratios, touch targets, design-token contrast safety, and Svelte-specific implementations. Use for accessibility audits, a11y implementation, ADA compliance, or inclusive design.

AI integration patterns for Angular applications using Genkit, Firebase AI Logic, or Gemini API. Includes streaming responses, tool calling, and RAG patterns. Use when building AI-powered features in Angular apps.

Modern Angular 21+ patterns including signals, standalone components, zoneless change detection, and new control flow syntax (@if, @for). Use for Angular architecture decisions, implementing components with latest APIs, computed signal chains, select binding, ngModel two-way binding, or CanDeactivate guard patterns.

Angular CLI and MCP server integration for AI-assisted development. Includes Web Codegen Scorer for code quality, CLI commands, and project scaffolding. Use when setting up Angular projects, running ng generate, or evaluating AI-generated code quality.

Integrating design systems (Material Design, Carbon, etc.) into existing sites while preserving brand identity and design tokens. Use for design system adoption, brand preservation, visual consistency improvements, and subtle UX enhancements. Call for any work involving design tokens, CSS token bridges, or component-level design system integration.

Material Design 3 patterns for chat widget components. Use for status indicators, input fields, empty states, message bubbles, or typing indicators in chat UIs.

Material Design 3 (Material You) patterns for dashboards and web apps. Use for M3 components, design tokens, color system, tonal elevation, navigation patterns, canonical layouts, or dashboard layouts. Covers Angular Material and Svelte implementations.

Svelte 5 and SvelteKit production patterns — runes-based reactivity, stores, Web Components, Shadow DOM, and performance optimization. Use for frontend architecture decisions or implementing complex UI components.

Cloud-native CI/CD patterns for GCP using Cloud Build, Cloud Deploy, and GitOps. Use for pipeline design, deployment strategies (canary, blue-green), artifact management, or automating deployments to Cloud Run and GKE.

Cloud Run deployment patterns for stateless, scalable Python services. Use when deploying to Cloud Run, configuring health checks, optimizing cold starts, or troubleshooting container issues.

Cloud SQL PostgreSQL infrastructure provisioning and operations. Machine type selection, storage sizing, HA configuration, backup strategies, VPC networking. Use when configuring Cloud SQL instances, planning database capacity, setting up backups, or designing high availability.

GCP cost engineering and financial operations. Analyze billing, optimize resources, manage budgets, reduce spending. Use when discussing GCP costs, budget optimization, pricing decisions, cost analysis, or spend management.

Cloud-native observability patterns for GCP using Cloud Monitoring, Cloud Logging, and SLO-based alerting. Use for metrics design, dashboard creation, burn-rate alerting, or implementing SRE practices.

GCP security hardening patterns including IAM best practices, Workload Identity Federation (WIF), zero trust architecture, binary authorization, and container security. Use for securing GCP resources, eliminating service account keys, or implementing defense in depth.