Claude Skills by peterbamuhigire

Use when designing agent tool catalogs, tool schemas, action gating, human approval, and human-in-the-loop control for agentic AI systems.

Use when designing AI analytics, dashboards, SaaS AI metrics, NLP analytics, predictive analytics, or executive AI insight workflows. Orchestrates the former granular AI analytics skills as references.

Use when designing or building AI-powered application systems — choosing architecture style, selecting components, structuring the AI stack, making build-vs-buy decisions, and planning multi-tenant AI module gating

Use when modeling, metering, attributing, billing, or controlling AI usage costs across tenants, plans, features, providers, and agent workloads.

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 building an AI/LLM evaluation harness, golden datasets, quality metrics, judge calibration, regression gates, production monitoring, drift detection, or user-feedback loops; use ai-llm-integration for provider calls.

Use when planning a controlled AI-feature rollout or experiment in multi-tenant SaaS: tenant/user feature flags, percentage and canary cohorts, holdout metrics, A/B tests of prompts or models, eval and SLO gates, automatic rollback, tenant opt-out and consent, or shadow mode for risky changes.

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 preventing, detecting, triaging, communicating, recovering from, or reviewing AI incidents, AI errors, RCA, and postmortems.

Use when integrating an LLM provider into an application with streaming, structured outputs, tool calls, embeddings, multi-model routing, retries, caching, and usage metering.

Use when designing or building an LLM gateway for provider abstraction, tenant-aware routing, fallbacks, quotas, residency, audit logging, cost capture, and kill-switch enforcement.

Use when building the observability stack for AI features in a multi-tenant SaaS — prompt/response tracing, semantic logging, replay tooling, "show me why this answer", per-stage latency/cost breakdown, ticket→trace tie-back, and dashboards that answer the operational questions (which tenant, which feature, which prompt version, which model).

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 writing, refining, or structuring prompts for AI-powered app features — system prompts, user prompt templates, few-shot examples, chain-of-thought, prompt versioning, and defensive prompting

Use when building features that answer questions from private data, documents,

Security checklist for AI-powered application features — prompt injection

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 designing or building HTTP APIs — spec-first OpenAPI workflow, REST conventions, versioning, auth model, rate limiting, idempotency keys, error envelope, and observability notes. Produces the OpenAPI contract plus error/auth/idempotency/observability artifacts that frontend, mobile, security, and reliability skills consume. For endpoint-level security review load `vibe-security-skill`; for GraphQL-specific hardening load `graphql-patterns` reference `references/graphql-security.md`.

Use when designing or reviewing multi-service, message-driven, or eventually

Use when designing, building, or operating GraphQL APIs with Apollo Server +

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 designing or reviewing relational or document-backed data architecture

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

Use when designing, implementing, administering, tuning, backing up, restoring, monitoring, or troubleshooting MySQL schemas and production systems; use database-reliability for datastore-independent SLO and recovery policy.

Use when designing, implementing, administering, tuning, backing up, restoring, monitoring, or troubleshooting PostgreSQL schemas and production systems; use database-reliability for datastore-independent SLO and recovery policy.

Use when building CI/CD pipelines with build, test, security, packaging, deployment stages, reusable workflows, short-lived cloud authentication, caching, promotion gates, and pipeline telemetry; use deployment-release-engineering for rollout decisions.

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 building or running production Kubernetes clusters, namespaces, workloads, ingress, autoscaling, multi-tenant RBAC, network/Pod Security, resource quotas, upgrades, certificates, etcd, metrics, disruption, and recovery.

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 designing or implementing double-entry accounting policy and an embedded ledger engine for invoices, payments, stock, balanced postings, mapped accounts, idempotency, reversals, period locks, audit trails, and financial statements.

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

Use when implementing IAS 21 multicurrency accounting: functional currency, presentation currency, transaction currency, exchange-rate tables, settlement, realised and unrealised forex gains or losses, revaluation, and currency-safe ledger design.

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 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 administering ArcGIS Enterprise or building real-estate-specific

Use when implementing GIS maps, spatial data services, maps integrations, geocoding, spatial APIs, or PostGIS-backed geospatial platforms. Load absorbed GIS mapping, maps integration, and PostGIS backend references as needed.

Use when building, architecting, or reviewing native iOS apps with Swift, SwiftUI, structured concurrency, module boundaries, security, tests, and performance; use platform-capabilities for Apple integrations and mobile-platform-operations for release.

StoreKit 2 in-app purchases, subscriptions, and monetization for iOS

Use when integrating iOS capabilities including App Intents, Spotlight, SwiftData, offline storage, biometrics, notifications, Bluetooth, media, PDF, Foundation Models, Core ML, or Vision; use ios-development for app architecture.

Use when designing or reviewing iOS authentication, Keychain, App Attest, privacy manifests, permissions, RBAC, tenant isolation, or AI security; use ios-development for general implementation.