chwezi-dev-engine

Top-level router for the Chwezi Core Systems web-development and software-engineering skills engine. Use for AI systems, SaaS, architecture, APIs, databases, security, frontend engineering, mobile, DevOps, reliability, product engineering, SDLC documentation, catalog maintenance, delivery evidence packs, routing fixtures, and world-class engineering quality gates.

Use when specifying or implementing engine-neutral gameplay systems such as movement, combat, AI, quests, dialogue, inventory, progression, save/load, world state, spawning, cameras, or narrative state; engine skills own framework integration.

Use when building, restructuring, profiling, testing, or packaging a Unity mobile game in C# for Android or iOS; covers project architecture, scenes, prefabs, data, input, assets, saves, builds, and Unity-specific release evidence.

Use when discovering, designing, prioritizing, or auditing AI-powered products for measurable business value. Applies to AI opportunity mapping, ROI cases, product strategy, client workshops, and deciding whether an AI feature should be built.

Use when specifying one AI-powered feature end to end, including model choice, prompt and context contracts, output schema, fallbacks, human oversight, UX states, and evaluation.

Use when discovering and ranking AI use cases for a project or module and producing an opportunity register with impact, effort, cost, risk, and evidence gaps.

Use when designing or building an AI-enhanced web app with chat, RAG, MCP tools, streaming, provider abstraction, feature gates, token budgets, and output guardrails.

Use when building Python agents with the OpenAI Agents SDK, including runners, tools, handoffs, guardrails, tracing, memory, multi-agent topology, and deterministic orchestration.

Use when building or reviewing native Android applications with Kotlin, Compose, Hilt, and layered architecture; use android-data-persistence or android-tdd for focused data and test work.

Use when designing or reviewing multi-service, message-driven, or eventually consistent systems. Covers service boundaries, consistency tradeoffs, event workflows, outbox and inbox patterns, sagas, ordering, and idempotency.

Use when designing, reviewing, or refactoring microservice boundaries, communication, service ownership, deployment independence, resilience, and distributed data flows. Load absorbed microservices fundamentals, models, communication, and resilience references as needed.

Use when defining or reviewing software architecture for web apps, mobile backends, SaaS platforms, APIs, distributed systems, or major features. Covers bounded contexts, module decomposition, contracts, failure handling, ADRs, and scalability tradeoffs.

Use when authoring or normalising a specialist skill, or preparing to ship a feature or release — defines the seven evidence categories every specialist skill must declare against and provides the canonical Release Evidence Bundle template. The contract spine that turns scattered validation skills into a coherent ship-readiness check.

Use when defining database SLOs, error budgets, backup verification, capacity policy, incident response, game days, or MySQL and PostgreSQL on-call practice.

Use when administering, tuning, backing up, restoring, monitoring, or troubleshooting PostgreSQL production systems. Load the absorbed PostgreSQL administration and performance reference files for operational runbooks, query tuning, vacuum, replication, and incident response.

Use when designing CI/CD pipelines, stage gates, reusable workflows, short-lived cloud authentication, caching, deployment strategies, and pipeline telemetry.

Use when designing cloud deployments, Dockerising applications, laying out AWS or GCP environments, choosing a deployment pattern, or moving a workload from a single VM to a resilient multi-AZ topology.

Use when designing or reviewing deployment pipelines, rollout strategies, release gates, rollback plans, migration-safe releases, and post-deploy verification for production systems. Covers build promotion, environment strategy, release evidence, and operational safety.

Use when containerizing PHP, Python, JavaScript, or API services with Dockerfiles, multi-stage images, Compose, CI builds, runtime permissions, and persistent dependencies.

Use when provisioning or changing cloud infrastructure with Terraform or Ansible — modules, remote state with S3 native locking, workspaces vs directory-per-env, common AWS patterns, idempotent Ansible roles for Debian/Ubuntu, GitOps with ArgoCD/Flux, drift detection, and Vault secret injection.

Use when running Kubernetes as a platform team — bootstrapping self-managed clusters on Debian/Ubuntu, designing multi-tenant RBAC, enforcing Pod Security and resource quotas, and operating cluster lifecycle (upgrades, certs, etcd, ingress, cert-manager, metrics-server). Self-managed first, cloud-managed second.

Use when designing or reviewing logs, metrics, traces, alerts, SLOs, dashboards, audit events, or production telemetry for web apps, APIs, SaaS platforms, mobile backends, and AI systems. Covers instrumentation strategy, diagnosis-first telemetry, alert quality, and operational visibility.

Use when designing or reviewing production reliability for APIs, SaaS platforms, background jobs, distributed workflows, mobile backends, or AI-enabled systems. Covers timeout and retry policy, degradation, queue safety, incident readiness, and recovery-aware design.

Use when coordinating accounting and finance implementation reviews, doctrine routing, control evidence, remediation priorities, and release decisions across a software system.

Use when defining, implementing, or auditing frontend performance for web apps and SaaS frontends; produces a per-flow performance budget, measurement plan tied to SLOs, and CI regression gate. Use api-design-first for API shape and observability-monitoring for server SLOs.

Use when implementing or reviewing web image compression before upload with Squoosh or Canvas and server-side Sharp validation. Use frontend-performance for broader page loading budgets and storage skills for object-store lifecycle policy.

Use when implementing or reviewing a Next.js App Router application with server and client components, route handlers, middleware, caching, authentication, streaming, or deployment. Use react-development for framework-neutral components and api-design-first for external APIs.

Use when implementing or reviewing React components, hooks, state ownership, forms, rendering performance, error boundaries, or component tests. Use nextjs-app-router for Next.js server boundaries and ux-content-strategy for product content systems.

Use when implementing or reviewing Tailwind CSS styling, responsive layouts, state variants, theme tokens, layers, grids, or build configuration. Use a design-system skill for visual direction and accessibility-wcag for formal accessibility review.

Use when planning, governing, or upgrading product content as a system - voice charts, content-first design, UI text patterns, form completion gates, error taxonomy, content measurement, decision communication, lifecycle narrative, and content operations. Higher-level orchestration above tactical microcopy and form mechanics.

Use when building or reviewing native iOS applications with Swift, SwiftUI, structured concurrency, security, tests, and performance gates; use focused iOS skills for persistence, release, or monetisation.

Use when writing or reviewing modern JavaScript for browser or PHP-backed SaaS applications, including modules, asynchronous flows, error handling, language features, and performance.

Use when building or reviewing Node.js servers, APIs, CLI tools, streams, asynchronous workflows, real-time systems, tests, scaling, or production deployment.

Use when writing or reviewing PHP 8+ applications, object-oriented domain code, Laravel services, PSR-compliant packages, secure request handling, tests, or performance-sensitive PHP.

Use when computing complex analytics, KPIs, cohort/funnel/retention metrics, financial math (IRR/NPV/amortization), statistical tests, anomaly detection, or geospatial analytics in Python — for cases where SQL alone gets unwieldy.

Use when building ETL jobs, document intelligence pipelines, OCR, PDF/Excel ingestion, image/media processing, or external-API sync pipelines in Python — idempotent scheduled jobs with validation, dead-letter queues, and multi-tenant isolation.

Use when adding forecasting, classification, regression, or anomaly detection to a SaaS feature — demand/sales/cash-flow forecasting, churn and risk scoring, anomaly detection — with scikit-learn, Prophet, and statsmodels. Covers data prep, model serving, monitoring, and explainability.

Use when building end-to-end TypeScript applications — Node backend (Fastify), React/Next frontend, shared types via tRPC or Zod, monorepo with turborepo/nx, Prisma/Drizzle data layer, end-to-end type safety.

Use when writing or reviewing website copy, articles, headlines, ledes, persuasive content, readability, or scannable structure.

Use when handling service recovery, escalations, complaints, apology language, frontline empowerment, CX measurement, or prevention loops.