Primitives

typescript-waf

TypeScript/JavaScript coding standards aligned with Azure WAF pillars — secure credential handling, async patterns, Zod validation, structured error handling, and production-ready testing with Vitest.

• security
• reliability
• performance-efficiency

uvicorn-waf

Uvicorn/ASGI standards — worker config, graceful shutdown, health checks, production settings.

• performance-efficiency
• reliability

vitest-waf

Vitest testing standards — ES2022, snapshot testing, coverage, and mock patterns for Node.js/TypeScript.

• reliability

winui3-waf

WinUI 3 standards — XAML, MVVM, Windows App SDK patterns.

• reliability
• performance-efficiency

wordpress-waf

WordPress development standards — hooks/filters, custom post types, security, and performance.

• security
• performance-efficiency

wpf-waf

WPF standards — MVVM, data binding, commands, styles, templates.

• reliability

xunit-waf

xUnit testing standards — Fact/Theory, FluentAssertions, and integration testing with WebApplicationFactory.

• reliability

zod-waf

Zod validation standards — schema design, type inference, transform, error messages, API input validation.

• security
• reliability

agent-chain-configure

Orchestrate builder, reviewer, and tuner agent handoffs for solution plays — define roles, model routing, token budgets, and quality gates

api-rate-limit-configure

Configure API rate limiting, APIM throttling, and retry behavior for AI endpoints — absorb bursts, isolate noisy tenants, and control 429 retries

app-insights-configure

Configure Application Insights, OpenTelemetry, and KQL dashboards for AI workloads — trace latency, token usage, failures, and cost signals

audit-log-implement

Implement immutable audit logging, PII redaction, and Sentinel monitoring for AI systems — preserve evidence, prove access history, and detect suspicious activity

azure-openai-setup

Set up Azure OpenAI deployments, RBAC, and monitoring — harden inference endpoints and control latency, quota, and cost

backup-restore-ai

Back up AI data, vector indexes, and configuration state — recover prompts, conversations, and search assets after failures

bicep-module-create

Create reusable Bicep modules, parameter files, and registry packages — standardize Azure infrastructure and reduce deployment drift

canary-deploy-ai

Implement canary deployment, rollout gates, and rollback automation for AI changes — catch latency or quality regressions before full release

circuit-breaker-add

Add a circuit breaker, fallback routing, and health checks for Azure OpenAI calls — contain 429 and 503 cascades and preserve service

compliance-audit-run

Run AI compliance audits, collect Azure evidence, and track remediation — assess SOC 2, HIPAA, ISO 27001, and EU AI Act controls

embedding-model-select

Select embedding models, dimensions, and hybrid search settings for vector workloads - balance recall, storage cost, and migration risk

fai-agent-chain-configure

Configure builder→reviewer→tuner agent chain with handoff rules, model assignment, and evaluation gates.

fai-agent-governance

Review agent safety controls, budget limits, and human escalation paths - approve only agents that stay bounded, observable, and policy-compliant

fai-agentic-eval

Run evaluator-optimizer loops for agents and prompts - score outputs, revise weak instructions, and stop only when quality thresholds hold

fai-api-docs-generator

Generate API reference docs, examples, and error catalogs from OpenAPI or code annotations - keep endpoint docs accurate, testable, and publishable

fai-api-endpoint-generator

Generate typed REST API endpoints with Zod/Pydantic input validation, RFC 7807 error responses, OpenAPI annotation, and Managed Identity auth — eliminating schema drift and IDOR vulnerabilities.