852 docs tagged with "auto-generated"

Browse all 12 FrootAI workflows.

Browse all 333 FrootAI skills.

Browse all 176 FrootAI instructions.

Browse all 77 FrootAI plugins.

Browse all 10 FrootAI hooks.

Browse all 238 FrootAI agents.

Accessibility standards — WCAG 2.2 AA compliance, semantic HTML, ARIA roles/properties, keyboard navigation, focus management, color contrast, screen reader com

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

Agent coding standards — ReAct loop, tool selection, memory management, circuit breaker on tools.

AI agent safety standards — fail-closed defaults, least-privilege tool access, human-in-the-loop for destructive actions, prompt injection defense, budget contr

Agentic OS standards — .github folder structure, 7 primitives, 4 layers, plugin packaging.

Autonomous RAG where the AI agent controls retrieval — decides when to search, which sources to query, iterates on results.

Play 21 patterns — Agentic RAG patterns — retrieval decision loop, multi-source routing, query refinement, self-evaluation.

AI Evaluation Suite — groundedness, coherence, relevance, fluency, and safety scoring. Build evaluation pipelines with Azure AI Evaluation SDK.

AI glossary consistency — use standard FAI terminology, avoid ambiguous AI terms in code comments.

Azure AI Landing Zone — subscription vending, network topology, RBAC, policy enforcement.

Advanced AI Landing Zone — multi-region deployment, private endpoints, Azure Firewall, DDoS protection, sovereign cloud patterns.

Play 11 patterns — Advanced landing zone — multi-region, ExpressRoute, Azure Firewall, Policy as Code, Defender for Cloud.

Play 02 patterns — Landing zone patterns — hub-spoke VNet, private endpoints on ALL PaaS, Managed Identity, tag enforcement, GPU quota.

AI Observability — distributed tracing for LLM calls, token usage dashboards, latency monitoring, evaluation score tracking.

Play 17 patterns — AI observability patterns — OpenTelemetry spans, token metrics, quality dashboards, alert thresholds.

AI prompt safety in application code — input sanitization, output validation, structured output enforcement, content filtering, token budget management, system

AI Search Portal — full-text and vector hybrid search with semantic ranking, faceted navigation, autocomplete.

Play 09 patterns — Search portal patterns — faceted search, semantic ranker, result rendering, analytics, personalization.

Anomaly Detection — real-time and batch anomaly detection for time-series, metrics, and log data. Uses Azure AI Anomaly Detector, custom ML models.

Play 20 patterns — Anomaly detection patterns — streaming analytics, statistical thresholds, ML models, alert routing.

Ansible automation standards — idempotent playbooks, secure vault usage, role structure, handler patterns, variable naming, error handling, molecule testing, an

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

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

Arch Linux packaging standards — PKGBUILD structure, makepkg rules, dependency management, package signing, AUR submission, namcap validation, split packages, s

Architecture Patterns — cloud design patterns, domain-driven design, microservices, event sourcing, CQRS.

ASP.NET Core 9 standards — Minimal APIs, DI, middleware pipeline, Entra ID auth, EF Core, health checks, rate limiting, output caching, and Azure-native integra

Astro framework standards — Islands Architecture, content collections, view transitions, SSG/SSR modes, image optimization, MDX, and deployment patterns.

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

Azure AI Document Intelligence standards — model selection, layout analysis, table/form extraction, custom models, batch processing, confidence thresholds, SDK

Azure AI Foundry config — Hub/Project RBAC, deployment types, evaluation pipeline, content filter config.

Azure AI Language standards — text analytics, NER, sentiment analysis, PII detection, summarization, CLU, custom text classification, healthcare NLP, SDK patter

Azure AI Services — OpenAI, AI Search, Document Intelligence, Language, Speech, Vision.

Azure AI Speech standards — STT (real-time + batch), TTS (neural voices, SSML, custom voice), speech translation, pronunciation assessment, speaker recognition,

Azure AI Vision standards — image analysis, OCR, custom classification, spatial analysis, and content safety patterns.

Azure App Service standards — deployment slots, scaling, authentication, monitoring, and security patterns.

Azure Bicep AVM (Azure Verified Modules) standards — module usage, parameter patterns, WAF-aligned infrastructure.

Azure Containers — AKS, Container Apps, Container Registry, and Dockerized deployment patterns. GPU workloads, KEDA autoscaling.

Azure Cosmos DB standards — global distribution, partitioning, consistency, RU optimization, vector search.

Azure Data Services — Cosmos DB, SQL Database, Blob Storage, Data Explorer, and Redis Cache patterns. Schema design, partition strategies.

Azure DevOps standards — YAML pipelines, environments, service connections, test management, boards.

Azure Front Door & WAF standards — global load balancing, WAF rules, caching, SSL offloading, origin protection.

Azure Functions standards — serverless compute, triggers, bindings, durable functions, cold start optimization.

Azure Identity & Security — Managed Identity, Key Vault, RBAC, Conditional Access.

Azure Infrastructure — landing zones, hub-spoke networking, private endpoints, Azure Policy, RBAC.

Azure Logic Apps standards — workflow automation, connectors, error handling, B2B integration.

Azure Messaging — Service Bus, Event Hubs, and Event Grid patterns for async communication, event sourcing.

Azure Monitoring — Application Insights, Log Analytics, KQL queries, alert rules, workbooks.

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

Azure Cache for Redis standards — caching patterns, data structures, pub/sub, clustering, security.

Azure Serverless — Functions, Logic Apps, Event Grid, and Durable Functions patterns. Event-driven architectures with consumption-based scaling.

Azure Static Web Apps standards — static hosting, serverless API, authentication, CI/CD, custom domains.

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

Bicep Code Best Practices standards — module design, naming, parameters, outputs, testing

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

Bicep infrastructure-as-code standards aligned with Azure WAF pillars — Azure Verified Modules, secure parameter handling, tagging conventions, production deplo

Blazor standards — Server/WebAssembly/United components, state, performance, security

AI-driven web task execution using Playwright MCP and GPT-4o Vision — navigate websites, extract data, fill forms.

Play 23 patterns — Browser automation patterns — domain allowlist, no credential entry, screenshot analysis, action limits.

Call Center Voice AI — real-time speech-to-text, intent classification, sentiment analysis.

Play 04 patterns — Voice AI patterns — Azure Speech SDK, real-time transcription, sentiment detection, turn-taking, noise handling.

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

CI/CD Automation — GitHub Actions, Azure DevOps pipelines, build matrices, deployment gates.

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

Clojure Waf standards — Clojure coding standards — REPL-driven, immutable data, pure functions, and spec for validation.

Code Quality — automated code review, refactoring suggestions, dead code removal, complexity analysis.

Code Review Waf standards — Code review standards — what to check, severity levels, constructive feedback, and merge blocking criteria.

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

Containerization Waf standards — Containerization standards — immutability, reproducible builds, health probes, 12-factor.

Content Moderation — real-time text, image, and multi-modal content safety with Azure AI Content Safety. Includes severity scoring.

Play 10 patterns — Content moderation patterns — Azure Content Safety, 4 harm categories, threshold tuning, human review pipeline.

Configure Azure Content Safety thresholds, blocklists, and prompt shields for AI apps - block unsafe inputs, detect jailbreaks, and monitor moderation drift

Content Safety Toolkit — Azure AI Content Safety integration, custom blocklists, severity thresholds, image moderation, prompt injection detection.

Context Engineering — maximize AI effectiveness with structured context, memory banks, knowledge wiring.

Context Engineering Waf standards — Context engineering standards — maximize Copilot effectiveness through structured instructions, examples, and constraints.

Copilot extensibility — Graph connectors, plugin manifest, action design, M365 integration patterns.

Copilot Studio Bot — custom copilot experiences with Microsoft Copilot Studio, Power Virtual Agents.

Play 08 patterns — Copilot Studio patterns — topics, generative answers, knowledge sources, channel deployment, Dataverse integration.

Copilot Studio Waf standards — Copilot Studio standards — topic design, generative answers, knowledge sources, channel config.

Copilot for Teams Extension — declarative agents, API plugins, message extensions.

Play 16 patterns — Teams extension patterns — adaptive cards, message extensions, bot framework, Teams toolkit.

Copilot Thought Logging Waf standards — Copilot thought logging — track reasoning process, tool selection rationale, confidence levels.

Cost Bicep standards — Bicep cost optimization — consumption SKUs, auto-shutdown, tags for cost centers, budget resources.

Create cost dashboards, budget alerts, and attribution views for AI workloads - track token spend by model, team, and tenant before overruns hit production

Cost-Optimized AI Gateway — intelligent model routing, token budget enforcement, request caching, rate limiting.

Play 14 patterns — AI gateway patterns — APIM policies, semantic cache, token metering, multi-backend retry, budget enforcement.

Python cost optimization — token budgets, model routing, caching, batch embedding, async for throughput.

TypeScript cost optimization — streaming responses, semantic cache, token metering, efficient serialization.

C++ coding standards — modern C++20/23, RAII, smart pointers, and safe concurrency patterns.

C# .NET Development — ASP.NET Core, Minimal API, Blazor, MAUI, EF Core, xUnit/NUnit testing.

C#/.NET MCP server development standards — ModelContextProtocol NuGet patterns, [McpServerTool] attributes, dependency injection, IHostedService lifecycle, and

C# MCP Development — build Model Context Protocol servers in C# with .NET SDK, ASP.NET Core hosting, dependency injection, and Azure deployment patterns.

C#/.NET coding standards aligned with Azure WAF pillars — Managed Identity, async patterns, dependency injection, structured logging, Pydantic-like validation w

Dart/Flutter coding standards — effective Dart, widget composition, state management, and null safety.

Optimize RAG chunking, overlap, and metadata boundaries - improve retrieval recall, reduce noisy context, and preserve citation quality

Database administration and optimization — PostgreSQL, SQL Server, Cosmos DB modeling, query optimization, migration planning, and data pipeline patterns.

Migrate AI data, embeddings, and index schemas with zero-downtime cutovers - preserve compatibility, validate every step, and keep rollback ready

Dataverse SDK standards — entity operations, metadata, batch requests, and Power Platform integration.

Debian/Ubuntu administration standards — apt, systemd, UFW firewall, and server hardening.

OOP design patterns — interface segregation, composition over inheritance, and SOLID principles.

Design System — UI components, design tokens, theming, responsive layouts, accessibility, animations, and form patterns. Build consistent.

Deterministic AI Agent — finite state machines, rule-based routing, guardrailed tool use.

Play 03 patterns — Deterministic AI patterns — temperature=0, structured output, grounding, citation, evaluation-driven reliability.

Determinism standards — temperature=0+seed, structured output, validation pipeline, grounding checks.

DevOps and on-call operations — incident triage, Azure resource diagnostics, KQL query generation, deployment automation.

Django standards — models, views, URLs, ORM queries, and security middleware patterns.

Docker Containerization — multi-stage builds, distroless images, BuildKit caching, health checks.

Containerize AI applications with multi-stage images, health probes, and secure runtime settings - ship smaller containers and safer deployments

Dockerfile standards — multi-stage builds, non-root user, minimal base images, and security scanning.

Document Intelligence — OCR, form extraction, table recognition.

Play 06 patterns — Document processing patterns — AI Document Intelligence, table extraction, OCR confidence, structured output.

.NET architecture standards — DDD, SOLID, clean architecture, CQRS, event sourcing.

Draw.io diagram standards — consistent styling, layers, export formats, and architecture diagram patterns.

Edge AI with Phi-4 — deploy small language models on edge devices, IoT hubs, and local inference servers. Quantization, ONNX optimization.

Play 19 patterns — Edge AI patterns — Phi-4 optimization, ONNX Runtime, quantization, batch size tuning, device constraints.

Entity Framework Core standards — migrations, query optimization, eager/lazy loading, concurrency handling.

Electron standards — IPC security, preload scripts, context isolation.

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

Production-grade Retrieval-Augmented Generation pipeline with Azure AI Search, OpenAI embeddings, Container Apps deployment, and WAF-aligned evalua...

Play 01 patterns — RAG-specific patterns — chunking strategy, embedding batch, hybrid search, citation enforcement, hallucination prevention.

Create evaluation pipelines, CI gates, and regression checks for AI systems - score groundedness, block regressions, and publish release verdicts

.NET MAUI cross-platform specialist — iOS, Android, Windows, macOS from single C# codebase, on-device AI inference (ONNX), MVVM architecture, and mobile-first A

Agent-to-Agent (A2A) protocol specialist — Google's agent interop standard, AgentCard discovery, task lifecycle, streaming artifacts, push notifications, and mu

Accessibility specialist — WCAG 2.2 AA/AAA compliance, ARIA 1.2 patterns, screen reader optimization, keyboard navigation, focus management, and inclusive desig

ADR writer — documents architecture decisions with MADR 3.0 template, context, alternatives, trade-off matrices, consequences, and WAF pillar impact analysis.

AG-UI protocol specialist — Agent-User Interaction standard, event-based rendering, streaming state updates, tool call lifecycle, and frontend integration for A

Agentic RAG builder — autonomous retrieval agent, multi-source fusion (Search+web+DB), iterative query refinement, citation pipeline, and reflection-based quali

Agentic RAG reviewer — retrieval autonomy audit, source selection review, iteration limit verification, citation accuracy check, and reflection quality assessme

Agentic RAG tuner — iteration depth config, source weight optimization, reflection threshold calibration, citation requirements, and per-query cost analysis.

Agentic retrieval specialist — autonomous source selection, iterative refinement with relevance scoring, multi-hop reasoning, query decomposition, and grounded

AI agents expert — ReAct loops, tool orchestration, memory tiers, multi-agent topologies (supervisor/pipeline/debate/swarm), agent determinism, and production g

AI infrastructure expert — GPU compute sizing (A100/H100), VRAM estimation, model serving (vLLM/TensorRT-LLM/Triton), AKS node pool design, PTU vs PAYG cost mod

AI Landing Zone Advanced builder — multi-region hub-spoke, Azure Firewall Premium with TLS/IDPS, policy-driven governance at scale, GPU quota orchestration, and

AI Landing Zone Advanced reviewer — multi-region networking audit, firewall rule review, policy compliance verification, GPU quota validation, and DR testing re

AI Landing Zone Advanced tuner — multi-region network sizing, firewall rule optimization, policy effect progression, GPU type selection, and DR cost optimizatio

AI Landing Zone builder — hub-spoke networking, private endpoints, Azure Firewall, DNS architecture, identity foundation, and governance baseline for enterprise

AI Landing Zone reviewer — network security audit, private endpoint verification, identity compliance, Azure Policy enforcement, and Bicep infrastructure review

AI Landing Zone tuner — network sizing, firewall rule optimization, SKU right-sizing, cost analysis, DR configuration, and production readiness verification.

AI Observability builder — Application Insights distributed tracing, KQL query library for AI metrics, Azure Workbooks dashboards, alerting rules, and FinOps te

AI Observability reviewer — telemetry coverage audit, KQL query accuracy, dashboard UX review, alert threshold calibration, and PII-in-logs verification.

AI Observability tuner — Log Analytics commitment tier selection, sampling rate config, alert threshold calibration, dashboard refresh optimization, and retenti

AI Search Portal builder — Azure AI Search index design, hybrid search with scoring profiles, faceted navigation, answer generation with citations, and auto-sug

AI Search Portal reviewer — index schema audit, search relevance testing, answer citation accuracy, facet UX review, and performance benchmarking.

AI Search Portal tuner — hybrid weight optimization, scoring profile calibration, reranker config, suggester tuning, and answer generation quality.

Angular 19+ specialist — signals-based reactivity, standalone components, SSR with hydration, zoneless change detection, control flow syntax, and AI chat compon

API gateway architect — Azure APIM patterns, rate limiting, token-based throttling, multi-region load balancing, backend circuit breakers, and cost-aware routin

Senior cloud-native solution architect — Azure Well-Architected Framework alignment, AI system design, multi-service integration, cost modeling, trade-off analy

Microsoft AutoGen multi-agent framework — ConversableAgent, GroupChat topologies, code execution sandboxing, nested chat orchestration, human-in-the-loop patter

Azure AI Foundry specialist — Hub/Project resource model, Model Catalog deployment, Prompt Flow orchestration, evaluation pipelines with groundedness and safety

Azure AI Search specialist — HNSW vector indexes, hybrid keyword+vector retrieval, semantic ranker, integrated vectorization pipelines, custom skillsets, scorin

Azure Kubernetes Service specialist — GPU node pools (A100/H100), NVIDIA device plugin, model serving with vLLM/TGI/Triton, HPA/KEDA autoscaling, and production

Azure API Management specialist — AI Gateway patterns, semantic caching, token metering, multi-backend load balancing, circuit breaker, rate limiting, and FinOp

Azure Front Door & CDN specialist — global content delivery, WAF policies, caching rules, edge optimization, SSL/TLS management, and Private Link origins for AI

Azure Container Apps specialist — serverless containers, Dapr sidecars, KEDA autoscaling, GPU workload profiles, scale-to-zero, and AI agent hosting patterns wi

Azure Cosmos DB specialist — partition key design, DiskANN vector search, multi-region writes, RU optimization, change feed processing, and conversation/session

Azure DevOps specialist — YAML multi-stage pipelines, environment protection rules, artifact feeds, workload identity federation, and AI-specific deployment qua

Azure Event Hubs specialist — partitioned event streaming, Kafka compatibility, Schema Registry governance, real-time AI inference pipelines, and high-throughpu

Azure Functions specialist — event-driven AI processing, Durable Functions for long-running agent orchestration, timer triggers for batch inference, and cold st

Azure identity and access management specialist — Entra ID, Managed Identity, DefaultAzureCredential, workload identity federation, RBAC, Conditional Access, an

Azure Key Vault specialist — secrets rotation, CMK encryption, certificate lifecycle, HSM-backed keys, Managed Identity integration, and zero-secret deployment

Azure Logic Apps specialist — low-code workflow automation, 1400+ connectors, AI integration actions, Durable orchestration, B2B/EDI, and enterprise integration

Azure Monitor specialist — Application Insights for AI distributed tracing, KQL for token analytics, custom dashboards for groundedness/coherence metrics, cost

Azure networking specialist — hub-spoke VNet design, Private Link for AI services, NSGs, Azure Firewall, DNS private zones, and zero-trust network architecture.

Azure OpenAI specialist — model deployment types (PTU/PAYG/Global), content filtering, structured output, token optimization, multi-region load balancing, and p

Azure Policy specialist — built-in/custom policy definitions, AI governance initiatives, compliance scanning, remediation tasks, and policy-as-code deployment p

Azure Service Bus specialist — queues, topics/subscriptions, dead-letter handling, session-based ordered messaging, saga patterns, and agent-to-agent communicat

Azure SQL specialist — Hyperscale, serverless auto-pause, native vector search, geo-replication, intelligent performance tuning, and AI integration patterns wit

Azure Storage specialist — Blob lifecycle tiers, ADLS Gen2 for data lakes, private endpoints, managed identity auth, and document/model artifact storage for AI

Batch processing specialist — Azure Batch pools, Global Batch API (50% cost savings), Durable Functions fan-out, large-scale document/embedding pipelines, and a

Blazor specialist — Server + WebAssembly + United (.NET 8+) render modes, streaming SSR, AI chat UI components, SignalR real-time, and Razor component architect

Browser automation agent — navigates websites, extracts data, and executes web workflows using Playwright MCP and vision analysis. Domain-restricted, no credent

Browser Agent builder — Playwright MCP integration, GPT-4o Vision page navigation, multi-step web task automation, form filling, data extraction, and domain-res

Browser Agent reviewer — domain allowlist verification, vision accuracy testing, credential security audit, error recovery review, and task completion validatio

Browser Agent tuner — screenshot resolution config, timeout calibration, retry strategy, domain allowlist management, and vision cost optimization.

Bun runtime specialist — ultra-fast JavaScript/TypeScript, built-in bundler, native SQLite, test runner, and HTTP server patterns for AI APIs and MCP servers.

C#/.NET specialist — modern C# 12+/.NET 9, Azure SDK integration, Semantic Kernel, async/await patterns, Polly resilience, minimal APIs, and AI-native applicati

C# MCP server development specialist — ModelContextProtocol NuGet package, [McpServerTool] attributes, dependency injection, stdio/SSE transport, and Azure-inte

Call Center Voice AI builder — STT→LLM→TTS streaming pipeline, Azure Communication Services, real-time transcription, intent classification, PII redaction, and

Call Center Voice AI reviewer — voice quality audit, pipeline latency review, PII redaction verification, TCPA compliance, and escalation trigger testing.

Call Center Voice AI tuner — speech config optimization, neural voice selection, latency tuning, escalation thresholds, cost-per-call analysis, and CSAT metric

AI capacity planning specialist — GPU sizing, PTU allocation, token volume forecasting, cost modeling, scaling strategy, and FinOps for Azure AI workloads.

CI/CD pipeline specialist — GitHub Actions with OIDC, multi-stage deployments, AI quality gates (eval.py), security scanning, and DORA metrics for AI applicatio

Cloudflare specialist — Workers AI for edge inference, Workers KV, D1 database, R2 storage, AI Gateway, and CDN optimization for AI application delivery.

Code review specialist — SOLID principles, clean code, OWASP security checks, AI-specific prompt injection auditing, and performance anti-pattern detection acro

Multi-agent debugging specialist — systematic root cause analysis, stack trace interpretation, Azure diagnostics, LLM-specific issue debugging, and performance

Multi-agent implementer — writes production code following TDD, implements features with Azure SDKs, generates Bicep infrastructure, and creates solution play c

Multi-agent orchestrator — routes tasks to specialist agents, manages turn limits, decomposes complex requests, synthesizes results, and ensures quality gates a

Multi-agent researcher — gathers information from knowledge bases, codebase search, documentation analysis, and web research to ground specialist agents with ve

Multi-agent reviewer — security audit, OWASP LLM Top 10, WAF compliance, code quality, AI safety checks, and PR review with severity-classified feedback.

Multi-agent tester — generates unit/integration/E2E tests, AI evaluation pipelines, mutation testing, and quality assurance for AI outputs with deterministic se

AI compliance specialist — EU AI Act risk classification, NIST AI RMF, GDPR data subject rights, HIPAA PHI handling, SOC 2 evidence collection, and Azure compli

Content Moderation builder — Azure Content Safety API integration, 4-category severity scoring, custom blocklists, APIM gateway middleware, and severity-based r

Content Moderation reviewer — safety coverage audit, severity threshold verification, blocklist completeness, bypass prevention, and human review workflow testi

Content Moderation tuner — per-category severity calibration, blocklist optimization, false positive reduction, routing distribution, and moderation cost analys

Content safety specialist — Azure AI Content Safety API, 4 harm categories with severity scoring, Prompt Shields for jailbreak defense, groundedness detection,

Microsoft Copilot ecosystem expert — M365 Copilot declarative agents, Copilot Studio, GitHub Copilot agent mode, Graph connectors, Adaptive Cards, and cross-pla

Copilot Studio Bot builder — declarative agent setup, topic design, SharePoint/Dataverse knowledge grounding, Power Platform connectors, and conversation guardr

Copilot Studio Bot reviewer — topic coverage audit, knowledge source validation, DLP compliance, guardrail verification, and conversation flow testing.

Copilot Studio Bot tuner — trigger phrase expansion, knowledge source optimization, response tone calibration, guardrail sensitivity, and conversation flow tuni

Copilot Teams Extension builder — M365 Copilot declarative agent, Microsoft Graph API integration, Adaptive Cards, Entra ID SSO, and Teams message extension dev

Copilot Teams Extension reviewer — Graph permission audit, SSO flow testing, Adaptive Card rendering review, message extension validation, and Teams policy comp

Copilot Teams Extension tuner — Graph scope minimization, knowledge source config, response tone calibration, Adaptive Card optimization, and permission tuning.

AI cost gateway specialist — APIM-based AI gateway with semantic caching, model routing by complexity, token budget enforcement, multi-region PTU load balancing

FinOps cost optimizer for AI workloads — model routing economics, semantic caching ROI, token budget design, PTU vs PAYG analysis, right-sizing recommendations,

Cost-Optimized AI Gateway builder — APIM AI gateway, semantic caching with Redis, smart model routing by complexity, token budget enforcement, and multi-region

Cost-Optimized AI Gateway reviewer — routing accuracy audit, cache quality verification, budget enforcement testing, security review, and cost savings validatio

Cost-Optimized AI Gateway tuner — semantic cache threshold calibration, routing complexity boundaries, token budget tiers, rate limits, and cost optimization an

CrewAI multi-agent framework specialist — crew composition, role-based agents with backstory, task delegation with expected output, sequential/hierarchical proc

Dapr distributed application runtime specialist — service invocation, state management, pub/sub messaging, bindings, secrets management, and sidecar-based AI mi

Data engineering specialist for AI — RAG ingestion pipelines, document chunking, ETL/ELT patterns, PII detection with Presidio, data quality scoring, and Azure

Datadog observability specialist — monitor creation, APM trace correlation, dashboard design, metric queries, and AI workload monitoring with custom metrics for

Systematic debugging specialist — reproduce-isolate-fix methodology, binary search isolation, stack trace interpretation, Application Insights transaction traci

Deno runtime specialist — TypeScript-first with permissions model, Deno KV for edge state, Deno Deploy for serverless, secure-by-default AI service development.

Deterministic Agent builder — zero-temperature architecture, seed pinning, structured JSON output, multi-layer guardrails, confidence scoring, and anti-hallucin

Deterministic Agent reviewer — reproducibility testing, guardrail completeness audit, anti-sycophancy verification, schema validation review, and confidence cal

Deterministic Agent tuner — confidence threshold optimization, guardrail severity calibration, evaluation metric tuning, retry config, and A/B testing for deter

Deterministic AI specialist — makes AI outputs reproducible, grounded, and auditable with temperature control, seed pinning, JSON schema output, RAG grounding,

DevOps lifecycle specialist — GitHub Actions OIDC, Infrastructure as Code (Bicep/Terraform), deployment strategies (blue-green/canary), SRE practices, DORA metr

Docker specialist — multi-stage builds, distroless images, GPU container support (CUDA/NVIDIA), ACR management, layer optimization, and container patterns for A

Document Intelligence builder — Azure AI Document Intelligence OCR, multi-format processing, GPT-4o field extraction, Cosmos DB storage, and validation pipeline

Document Intelligence reviewer — OCR accuracy audit, schema validation, PII handling review, pipeline error handling, and confidence threshold verification.

Document Intelligence tuner — OCR settings optimization, extraction confidence calibration, custom model training data, batch performance, and cost-per-document

Document Processing builder — GPT-4o Vision multi-modal analysis, Azure Document Intelligence, table extraction, classification pipeline, and PII-aware storage.

Document Processing reviewer — multi-modal extraction accuracy audit, table parsing quality, PII masking verification, pipeline error handling, and classificati

Document Processing tuner — GPT-4o Vision resolution settings, extraction confidence calibration, table detection thresholds, chart parsing config, and batch pe

DSPy framework specialist — declarative LM programs, signature-based modules, optimizers (BootstrapFewShot, MIPRO), assertions, metric-driven prompt optimizatio

Edge AI builder — Phi-4 on-device inference, ONNX quantization (INT4/INT8), Azure IoT Hub fleet management, offline-first architecture, and cloud fallback patte

Edge AI reviewer — quantized model quality audit, offline resilience testing, fleet rollout verification, cloud fallback review, and device security checks.

Edge AI tuner — quantization level selection, on-device latency optimization, sync schedule config, cloud fallback thresholds, and per-device cost analysis.

Elasticsearch specialist — index design, BM25 + kNN hybrid search, vector fields with HNSW, ILM lifecycle, cluster management, and RAG integration patterns.

Embedding specialist — text-embedding-3 model selection, Matryoshka dimension reduction, batch embedding pipelines, similarity metrics, chunking strategies, and

Enterprise RAG builder — hybrid search pipeline (BM25+vector), Azure AI Search indexing, OpenAI chat completions with citations, chunking strategies, and evalua

Enterprise RAG reviewer — RAG quality audit, citation accuracy, search config validation, security compliance, OWASP LLM Top 10, and WAF pillar alignment checks

Enterprise RAG tuner — config optimization for search quality, token costs, chunking parameters, evaluation thresholds, and model selection economics.

Epic breakdown specialist — decomposes large AI features into INVEST user stories with acceptance criteria, sprint-sized tasks, dependency mapping, and WSJF pri

Event-driven architecture specialist — Azure Event Grid, Service Bus, Event Hubs selection, event sourcing, CQRS, saga orchestration, and exactly-once processin

Fine-tuning and MLOps specialist — LoRA/QLoRA techniques, JSONL training data preparation, Azure OpenAI fine-tuning workflow, hyperparameter tuning, evaluation-

Fine-Tuning Workflow builder — Azure OpenAI fine-tuning, JSONL data preparation, LoRA/QLoRA techniques, MLflow experiment tracking, evaluation-driven iteration,

Fine-Tuning Workflow reviewer — training data quality audit, hyperparameter validation, evaluation methodology review, safety retesting, and alignment preservat

Fine-Tuning Workflow tuner — learning rate scheduling, LoRA rank/alpha optimization, epoch calibration, batch sizing, data quality filtering, and training cost

GenAI foundations expert — transformer architecture, tokenization, inference optimization (KV cache, speculative decoding), model taxonomy, prompt engineering t

Git workflow specialist — trunk-based development, conventional commits, PR best practices, branch protection, merge strategies, CODEOWNERS, and Git hooks for A

GitHub Actions specialist — OIDC federation to Azure, reusable workflows, matrix strategies, composite actions, caching, security hardening, and AI-specific CI/

Go development specialist — idiomatic Go 1.22+, goroutines/channels concurrency, Azure SDK for Go, high-performance HTTP servers, error handling patterns, and t

Go MCP server specialist — mcp-go SDK, struct-based tool definitions, context-aware handlers, stdio transport, concurrent tool execution, and Azure service inte

GraphQL specialist — schema design, resolver patterns, DataLoader N+1 prevention, subscriptions for AI streaming, federation, query complexity limits, and code

GraphRAG specialist — entity extraction, relationship mapping, knowledge graph construction, community detection, graph-based retrieval with Cosmos DB Gremlin/N

gRPC specialist — Protocol Buffers schema design, unary/streaming RPCs, interceptors for auth and tracing, load balancing, health checking, and high-performance

Microsoft Guidance specialist — constrained generation, token healing, regex patterns, guaranteed JSON/XML compliance, select/gen/each primitives, and grammar-e

htmx specialist — HTML-over-the-wire, hx-get/hx-post/hx-swap, server-sent events for AI streaming, progressive enhancement, and minimal-JavaScript AI chat inter

Internationalization specialist — multi-language AI responses, ICU message format, locale-aware formatting, Azure Translator integration, RTL support, and trans

Incident response specialist — severity classification (P0-P4), triage protocols, automated runbooks, war room coordination, root cause analysis, blameless post

IT Ticket Resolution builder — event-driven classification pipeline, auto-resolution via knowledge base, ServiceNow/Jira integration, skill-based routing, and S

IT Ticket Resolution reviewer — classification accuracy audit, auto-resolution quality, routing fairness, SLA compliance, ServiceNow integration security, and P

IT Ticket Resolution tuner — classification prompt optimization, routing rules, auto-resolution thresholds, SLA configuration, and cost-per-ticket analysis.

Java/Spring Boot specialist — Java 21+ virtual threads, Spring Boot 3.3, Spring AI for LLM integration, reactive streams for SSE, Azure SDK, and enterprise-grad

Java MCP server specialist — MCP SDK for Java, Spring Boot auto-configuration, @Tool annotation, reactive streams, enterprise service patterns, and Azure integr

Jira integration specialist — AI-powered ticket triage, sprint query automation, board management, release tracking, and project management workflow design.

Kotlin specialist — coroutines with structured concurrency, Ktor HTTP server, Flow for reactive AI streaming, Jetpack Compose UI, and Azure SDK suspend-friendly

Kotlin MCP server specialist — coroutine-based tool handlers, Ktor server transport, sealed class tool definitions, Flow-based streaming, and Azure suspend-frie

Kubernetes specialist — pod scheduling, GPU resource management, network policies, Helm charts, GitOps with Flux/ArgoCD, and production-grade AI workload orches

Azure AI Landing Zone architect — hub-spoke networking, private endpoints for all PaaS, managed identity, GPU quotas, governance policies, and Bicep-based enter

LangChain framework specialist — LCEL expression language, chains, agents with tool use, retrievers, memory, callbacks, LangSmith tracing, and production RAG pi

LlamaIndex data framework specialist — document loaders, index types (VectorStore/Summary/Knowledge Graph), query engines, response synthesizers, and agent tool

LLM landscape expert — model families (GPT, Claude, Llama, Gemini, Phi), benchmarks (MMLU, HumanEval, MT-Bench), deployment types, quantization, and model selec

Markdown specialist — CommonMark/GFM, agent markup (.agent.md/.instructions.md/SKILL.md), documentation standards (README/ADR/changelog), accessibility, and con

MCP protocol expert — Model Context Protocol specification, tool/resource/prompt primitives, stdio/SSE transports, server development patterns, and MCP ecosyste

Developer mentoring specialist — Socratic teaching, personalized learning paths, constructive code review feedback, skill gap analysis, and progressive complexi

Mermaid diagram specialist — flowcharts, sequence diagrams, architecture diagrams, ER diagrams, state machines, and Gantt charts for AI system documentation.

Migration specialist — legacy-to-cloud, .NET Framework upgrade, database migration, AI-native re-architecture, 6R framework, Azure Migrate, and incremental migr

ML engineering specialist — model training pipelines, LoRA/QLoRA fine-tuning, evaluation metrics, MLOps with Azure AI Foundry, model registry, and serving optim

MLflow specialist — experiment tracking, model registry, metric/artifact logging, Azure ML integration, deployment pipelines, and model lifecycle management.

Model Serving AKS builder — GPU cluster design, vLLM/TGI serving engines, NVIDIA device plugin, HPA/KEDA autoscaling, model versioning, and canary deployments.

Model Serving AKS reviewer — GPU cluster audit, vLLM config validation, autoscaling verification, pod security review, and inference latency benchmarking.

Model Serving AKS tuner — GPU SKU selection, vLLM memory/batching optimization, quantization decisions, autoscaling thresholds, and inference cost analysis.

MongoDB specialist — document schema design, aggregation pipelines, Atlas Vector Search for RAG, Cosmos DB MongoDB vCore, change streams, and AI application dat

Multi-Agent Service builder — supervisor orchestration pattern, agent registry, shared state via Cosmos DB/Redis, Dapr integration, tool routing, and loop preve

Multi-Agent Service reviewer — orchestration logic audit, state management review, loop prevention verification, agent security boundaries, and Dapr configurati

Multi-Agent Service tuner — supervisor routing config, per-agent token budgets, loop limits, model selection per role, memory TTL, and orchestration cost analys

NATS messaging specialist — JetStream for durable streams, key-value store, object store, request-reply, pub-sub, and lightweight event-driven AI microservice c

Neon serverless Postgres specialist — database branching, auto-scaling compute, pgvector for AI embeddings, connection pooling, and database-per-branch developm

OpenAPI specialist — API-first design, OpenAPI 3.1 spec authoring, code generation, validation middleware, and Copilot plugin API definition for AI applications

OpenTelemetry specialist — distributed tracing, metrics, logs with OTLP protocol, auto-instrumentation, custom spans for AI pipelines, and Azure Monitor exporte

PagerDuty incident management specialist — alert routing, escalation policies, on-call scheduling, automated incident creation, and AI-specific runbook integrat

Performance profiling specialist — latency analysis (P50/P95/P99), token optimization, GPU utilization profiling, bottleneck identification, cold start analysis

PHP 8.3+ specialist — modern PHP with attributes, typed properties, enums, fibers, Composer PSR standards, Laravel/Symfony patterns, and PHP-based AI API integr

PHP MCP server specialist — PHP 8.3+ attributes for tool registration, PSR standards, Composer dependency management, typed properties for JSON Schema, and stdi

FAI play dispatcher — routes user requests to the correct solution play based on intent classification, understands all 101 plays and their domains, delegates t

FAI play lifecycle manager — handles play initialization (scaffold file structure), Bicep deployment, evaluation quality gates, and config tuning for any of the

PostgreSQL specialist — pgvector for embedding storage, HNSW/IVFFlat indexes, query optimization with EXPLAIN ANALYZE, connection pooling (PgBouncer), partition

Power BI specialist — star schema data modeling, DAX formulas, report design, DirectQuery vs Import, AI-powered analytics with Azure OpenAI integration, and per

Power Platform specialist — Power Apps (Canvas + Model-driven), Power Automate cloud flows, Dataverse, custom connectors, DLP policies, and Copilot Studio integ

PRD writer — produces structured Product Requirements Documents with user personas, success metrics, AI-specific requirements (quality thresholds, safety), cons

AI product management specialist — requirements gathering, AI use case prioritization, evaluation metric design, go-to-market strategy, and responsible AI impac

Production AI patterns expert — hosting selection (Container Apps/AKS/Functions), APIM gateway patterns, streaming SSE, retry/circuit-breaker, health checks, an

Prompt engineering specialist — system message design, few-shot patterns, chain-of-thought, structured output schemas, anti-hallucination techniques, and evalua

Prompt Optimization builder — prompt versioning with semantic versions, A/B testing framework, Azure Prompt Flow, template engine with variable injection, and e

Prompt Optimization reviewer — version management audit, A/B test methodology review, template injection safety, evaluation pipeline validation, and prompt qual

Prompt Optimization tuner — system message clarity, few-shot example selection, A/B test config, template variable defaults, and prompt cost-quality trade-off a

Protocol Buffers specialist — proto3 schema design, backward compatible evolution, gRPC service definitions, code generation, and binary serialization for high-

Python development specialist — Python 3.12+, async/await patterns, Pydantic v2, FastAPI, pytest, type hints, Azure SDK, and production-grade AI application pat

Python MCP server specialist — FastMCP framework, @mcp.tool() decorators, async handlers, Pydantic input models, uv deployment, and Azure service integration fo

Qwik framework specialist — resumability (zero hydration), lazy loading, QwikCity routing, Island architecture, and instant-on AI-powered web applications.

Enterprise RAG architecture specialist — designs end-to-end retrieval-augmented generation pipelines with Azure AI Search, OpenAI embeddings, chunking strategie

RAG expert — advanced retrieval patterns (agentic, graph, multi-modal RAG), chunking strategies, hybrid search, re-ranking, evaluation metrics, and production R

Ray distributed computing specialist — Ray Serve for model serving, Ray Tune for hyperparameter optimization, Ray Data for preprocessing, and distributed traini

React/Next.js specialist — React 19 Server Components, Suspense streaming for AI chat, App Router, Tailwind CSS, useActionState, and accessibility-first pattern

Real-Time Analytics builder — Event Hub partitioned ingestion, Stream Analytics windowing, LLM-powered anomaly explanation, multi-signal scoring, and live dashb

Real-Time Analytics reviewer — ingestion reliability audit, windowing correctness, anomaly detection accuracy, scoring logic review, and alert quality verificat

Real-Time Analytics tuner — window size optimization, anomaly threshold calibration, baseline window selection, alert severity rules, and streaming cost analysi

AI red teaming specialist — prompt injection testing, jailbreak simulation, PyRIT automation, bias detection, adversarial dataset creation, and OWASP LLM Top 10

Redis specialist — caching patterns (TTL, LRU), semantic cache for AI (embedding similarity), pub/sub messaging, Redis Streams, and session storage for chat app

Code refactoring specialist — extract method, reduce cyclomatic complexity, improve testability, SOLID principles, design pattern application, and safe behavior

Remix framework specialist — nested routing, loaders/actions, progressive enhancement, streaming SSR, error boundaries, and AI-integrated full-stack patterns.

Responsible AI specialist — bias detection, fairness metrics, transparency requirements, EU AI Act compliance, content safety, groundedness evaluation, and AI g

Ruby 3.3+ specialist — pattern matching, Ractor concurrency, block DSL patterns, Rails 8, RuboCop standards, and AI API integration with httprb and ActiveJob.

Ruby MCP server specialist — mcp-rb gem, block DSL tool definitions, Rails integration, idiomatic Ruby patterns, and stdio transport for AI tool development.

Rust specialist — ownership/borrowing, async with tokio, serde serialization, error handling with thiserror/anyhow, and high-performance AI infrastructure (infe

Rust MCP server specialist — rmcp SDK, tokio async handlers, proc macro tool registration, serde for schemas, and ultra-high-performance MCP tool serving.

Salesforce specialist — Apex development, Lightning Web Components, Flow automation, Einstein AI, and enterprise CRM integration patterns with Azure OpenAI.

SAP integration specialist — SAP BTP, OData APIs, BAPI/RFC connectors, procurement/inventory/order processing, and AI-enhanced enterprise resource planning.

Security reviewer — audits code, infrastructure, and AI pipelines against OWASP Top 10, OWASP LLM Top 10, Azure security baselines, managed identity compliance,

Semantic Kernel specialist — plugins with function calling, KernelFilter middleware, memory/vector stores, agent group chat orchestration, and RAG pipeline patt

SEO specialist — structured data (JSON-LD), Core Web Vitals optimization, AI-generated content SEO, meta tags, sitemap generation, and search engine visibility

ServiceNow ITSM integration specialist — incident/change/request management via REST API, CMDB queries, knowledge base search, AI-powered ticket triage, and ser

Slack integration specialist — Bot API, Block Kit UI, slash commands, interactive modals, AI-powered conversation summarization, thread-based notifications, and

SolidJS specialist — fine-grained reactivity with signals, stores, createResource for AI data fetching, SolidStart SSR, and high-performance UI patterns.

Cloud solutions architect — end-to-end AI solution design, Azure service selection, multi-service integration, cost estimation, WAF trade-off analysis, and arch

Specification writer — generates AI-ready technical specifications with requirements, evaluation criteria, WAF alignment, API contracts, data models, and accept

SQL Server specialist — on-premises SQL Server, Always On Availability Groups, query optimization with EXPLAIN, and structured data integration for AI pipelines

Real-time streaming specialist — SSE for LLM token delivery, WebSocket for bidirectional chat, ReadableStream API, backpressure handling, and Azure Event Hubs s

Supabase specialist — pgvector for AI embeddings, real-time subscriptions, Edge Functions (Deno), Row Level Security, Storage for documents, and Auth for user m

Svelte 5 specialist — runes ($state, $derived, $effect), SvelteKit routing, server load functions, streaming SSR, and minimal-bundle AI chat interfaces.

Swarm Orchestration builder — mesh/star/hierarchical agent topologies, supervisor task decomposition, agent specialization, shared memory via Cosmos DB, and con

Swarm Orchestration reviewer — topology audit, supervisor logic review, agent specialization validation, shared memory consistency, and conflict resolution test

Swarm Orchestration tuner — topology selection, agent count optimization, consensus config, memory TTL calibration, and per-agent budget allocation.

Multi-agent swarm supervisor — routes tasks to specialist agents, manages turn limits and token budgets, handles agent coordination, conflict resolution, and sy

Swift specialist — structured concurrency (async/await, TaskGroup, actors), SwiftUI, Codable, and Apple platform AI integration with on-device Core ML and cloud

Swift MCP server specialist — actors for concurrency, Codable for JSON Schema, async/await handlers, and Apple platform MCP tool development.

TDD Green phase specialist — writes the minimal implementation to make failing tests pass, no more and no less. Follows the Red-Green-Refactor cycle.

TDD Red phase specialist — writes failing tests from requirements before any implementation. Covers happy path, error cases, edge cases, and AI-specific test sc

TDD Refactor phase specialist — improves code quality while keeping ALL tests green. Applies extract method, reduce complexity, improve naming, and design patte

Microsoft Teams integration specialist — Adaptive Cards, Bot Framework SDK, Graph API for channels/chats/meetings, AI-powered meeting summarization, and action

Tech debt analyst — identifies, quantifies, and prioritizes technical debt with cost-of-delay analysis, remediation plans, and sprint allocation recommendations

Technical documentation specialist — Diátaxis framework (tutorials/how-to/reference/explanation), API documentation, architecture docs, Mermaid diagrams, and RE

Temporal workflow orchestration specialist — durable execution, saga patterns, long-running AI workflows, activity retry policies, timeouts, and distributed tas

Terraform specialist — Azure provider, state management, module design, plan/apply workflow, drift detection, and multi-environment infrastructure deployment.

Test generation specialist — creates unit, integration, and E2E tests across Python (pytest), TypeScript (vitest), C# (xUnit), with AI-specific test patterns (g

Test planning specialist — designs test strategy, identifies coverage gaps, prioritizes test types (unit/integration/E2E/AI eval), and creates test plans with r

Test execution specialist — runs test suites, interprets results, identifies flaky tests, diagnoses failures, and reports coverage with actionable recommendatio

Turso specialist — libSQL (SQLite fork), edge replication, embedded vector search, multi-tenant databases, and low-latency AI data patterns.

TypeScript/Node.js specialist — strict mode, Zod validation, ESM modules, Vitest testing, Azure SDK integration, async patterns, and production-ready AI applica

TypeScript MCP server specialist — @modelcontextprotocol/sdk, McpServer class, Zod schema validation, async tool handlers, stdio/SSE transport, and npm distribu

AI UX designer — conversation design patterns, chatbot interaction flows, AI disclosure/transparency, loading states for streaming, confidence display, and acce

Vector database specialist — HNSW vs IVFFlat index selection, embedding storage with Qdrant/Pinecone/pgvector/Azure AI Search, similarity metrics, and performan

Vercel specialist — AI SDK (streaming useChat/useCompletion), Edge Functions, Next.js deployment, KV/Blob/Postgres storage, and serverless AI application patter

Vue.js 3 specialist — Composition API with script setup, Pinia state management, Nuxt 3 SSR/SSG, reactive streaming for AI chat, and TypeScript-first component

Weights & Biases specialist — experiment tracking, model versioning, hyperparameter sweeps, prompt tracing, evaluation dashboards, and LLM fine-tuning monitorin

WebAssembly specialist — WASI preview 2, Component Model, edge AI inference with Spin/Fermyon, Wasmtime runtime, and portable, sandboxed AI model execution.

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

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

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

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

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

Configure API rate limiting with Azure APIM policies, throttling tiers, and retry headers.

Configure Application Insights with custom AI metrics, anomaly alerts, and operational dashboards.

Generate solution architecture blueprints with Mermaid service topology, component responsibility tables, data flow annotations, and WAF pillar mapping — bridgi

Generate Architecture Decision Records capturing context, forces, decision rationale, rejected alternatives, and consequences — preventing knowledge rot when te

Wire .NET Aspire AppHost for multi-container orchestration, automatic service discovery, distributed OpenTelemetry export, and local Azure emulator integration

Scaffold ASP.NET Core Minimal API with typed route groups, FluentValidation, Managed Identity credentials, OpenAPI v3 via Scalar, Serilog structured logging, an

Implement immutable audit logging with Azure Blob Storage, Sentinel integration, and compliance evidence.

Analyze Azure AI workload spend with Cost Management API queries, flag overprovisioned PTU, identify semantic cache gaps, right-size model SKUs, and produce act

Provision Azure AI Foundry Hub and Project with Managed Identity RBAC, private endpoint networking, connected Azure AI Services and Key Vault — ready for Prompt

Create Azure AI Search vector indexes with HNSW profiles, semantic ranker configuration, hybrid BM25+vector search, field mappings for chunked RAG documents, an

Wire Azure App Configuration with feature flag targeting filters, Key Vault reference chaining, .NET/Python SDK refresh polling, and blue/green rollout strategi

Conduct Azure Well-Architected Framework reviews with scored pillar assessments, tiered finding severity, remediation priority tables, and an executive scorecar

Design and apply Azure Blob Storage lifecycle management policies with tiering to cool/archive, retention rules, and delete-after-N-days automation — reducing s

Integrate Language, Speech, Vision, and Translator services with Managed Identity authentication, pre-built and custom models, content safety filters, and regio

Configure Azure Container Registry with geo-replication across regions, image scanning for vulnerabilities, Managed Identity pull access, and OCI artifact suppo

Design Cosmos DB data models with optimal partition keys, Request Unit (RU) estimation, vector search embedding storage, and analytical workload isolation — exc

Configure Azure Data Explorer for real-time telemetry ingestion with KQL queries, time-series aggregations, and interactive dashboards — analyzing AI workload m

Configure Azure Event Grid for event-driven AI pipelines with topic subscriptions, dead-letter queues, retry policies, and role-based filtering — routing docume

Configure Azure Event Hubs for real-time data ingestion with stream processing, auto-scaling, Managed Identity auth, and consumer groups — enabling AI workload

Scaffold Azure Functions apps with HTTP/Event Hub/Service Bus triggers, input/output bindings, Managed Identity, Application Insights, and local development set

Configure Azure Key Vault with managed identities, RBAC, secret rotation policies, customer-managed keys (CMK), and app integration patterns — avoiding hardcode

Deploy Azure OpenAI with model selection, PTU vs PAYG pricing tiers, content safety filters, token management strategies, and streaming patterns — maximizing co

Set up Azure OpenAI Service with model deployments, RBAC, content filtering, and monitoring.

Query Azure Resource Graph across subscriptions with KQL for compliance audits, cost analysis, RBAC reviews, and cross-tenant resource discovery — enabling unif

Diagnose Azure resource health issues via Resource Health events, platform metrics, activity logs, and one-click remediation workflows — preventing cascading AI

|

|

|

|

|

|

Set up backup and restore procedures for AI application data, model configs, and index state.

|

Create a reusable Bicep module with typed parameters, conditions, outputs, and AVM alignment.

|

Analyze and refine prompts with specificity scoring, few-shot examples, and constraint encoding — improving accuracy by 20-40% and reducing token spend by 15-25

Build autonomous agent loops with ReAct pattern, tool calling, reflection cycles, and termination conditions — enabling multi-turn reasoning without callback he

Create reusable Bicep modules following AVM patterns with typed parameters, outputs, deployment tests, and registry publishing — standardizing infrastructure ac

Build optimized Docker images with multi-stage builds, non-root runtime, health checks, and AI model weight caching — reducing deployment time by 60% and image

Build custom LLM evaluation metrics for groundedness, coherence, relevance, and domain-specific quality — enabling automated CI gates and production quality mon

Build NoSQL data models (Cosmos DB documents, partition keys) for AI workloads with optimal consistency and throughput.

Build end-to-end prompting systems using Prompt Flow, versioning, A/B testing, and performance tracking.

Implement semantic search with embeddings, reranking, and hybrid search combining BM25 + vector similarity.

Migrate SQL schemas to cloud with zero downtime, validation, and rollback automation.

Create reusable Terraform modules for multi-cloud AI infrastructure provisioning.

Build comprehensive test harnesses for LLM applications covering deterministic and non-deterministic flows.

Implement custom tokenizers for domain-specific AI models optimizing vocabulary size and encoding efficiency.

Write effective unit tests for AI functions covering happy path, edge cases, and error handling.

Provision vector stores (Cosmos DB, Pinecone, Weaviate) with scaling, indexing, and retrieval optimization.

Implement canary deployment for AI model updates with traffic splitting and rollback on quality drop.

Generate automated changelogs from commit messages and PRs with structured formatting.

Add circuit breaker pattern for Azure OpenAI calls with exponential backoff and fallback behavior.

Apply cloud design patterns (bulkhead, retry, circuit breaker, CQRS) for AI workloads.

Analyze Python/TypeScript code for smell patterns and suggest refactoring opportunities.

Configure CodeQL for security scanning of ML/AI code against OWASP LLM Top 10.

Auto-generate code tutorials from comments and docstrings with executable examples.

Run a compliance audit against HIPAA, FedRAMP, SOC 2, and EU AI Act requirements for AI systems.

Generate component documentation from code annotations and type signatures.

Containerize ASP.NET Core AI APIs with Dockerfile multi-stage builds and health checks.

Containerize legacy ASP.NET Framework apps for cloud deployment.

Review AI-generated content against safety policies and compliance requirements.

Visualize architecture context maps showing bounded domains and integration points.

Implement contextual RAG with dynamic prompt augmentation based on user context and conversation history.

Include FAI.dev repo stats

Enforce conventional commits for automated changelog, versioning, and release notes generation.

Set up GitHub Copilot CLI for code generation, explanation, and commit message assistance.

Generate custom Copilot instructions for domain-specific coding patterns and conventions.

Integrate Copilot SDK into applications for AI-assisted features and chat capabilities.

Configure Copilot Spaces for team-based collaborative AI development environments.

Track Copilot usage metrics for cost attribution, productivity analysis, and adoption monitoring.

Design Cosmos DB data models with optimal partition keys, throughput, and vector indexes.

Build cost estimation models for AI workloads across Azure, models, and infrastructure.

Daily ecosystem health summary — primitive counts, marketplace stats, validation status, and recent changes across agents, instructions, skills, hooks, and plug

Automate daily prep workflows: code audits, test coverage checks, dependency updates.

Design database schemas with normalization, indexing, and partition strategies for AI workloads.

Identify and remove dead code paths in Python/TypeScript applications with automated tooling.

Deploy Enterprise RAG solution play with orchestration, monitoring, and scaling.

Deploy AI Landing Zone infrastructure with networking, governance, and compliance.

Deploy Deterministic Agent with structured output validation and evaluation gates.

Deploy Call Center Voice AI with STT, LLM, TTS streaming pipeline.

Deploy IT Ticket Resolution automation with multi-agent orchestration.

Deploy Document Intelligence solution with OCR and entity extraction.

Deploy Multi-Agent Service coordinator with agent delegation and state management.

Deploy Copilot Studio bot with custom actions and conversation flows.

Deploy AI Search Portal with semantic ranking, hybrid search, and result reranking.

Deploy Content Moderation system with safety scoring and policy enforcement.

Deploy Advanced AI Landing Zone with hub-spoke networking and compliance.

Deploy Model Serving on AKS with GPU scheduling and autoscaling.

Deploy Fine-Tuning workflow with JSONL data prep and evaluation gates.

Deploy Cost-Optimized Gateway with model routing and caching.

Deploy Multi-Modal Document Processing with vision and layout analysis.

Deploy Copilot Teams Extension with custom actions and bot framework.

Deploy AI Observability stack with KQL, dashboards, and alerting.

Deploy Prompt Management system with versioning and A/B testing.

Deploy Phi4 models on edge devices with quantization and local inference.

Deploy Anomaly Detection system using statistical and ML methods.

Deploy Agentic RAG with tool use and dynamic retrieval.

Deploy Multi-Agent Swarm coordinator with topology and state sync.

Deploy Browser Automation Agent with Selenium and Playwright.

Run preflight checks before deploying solution play infrastructure.

Design accessible AI interfaces following WCAG 2.1 AA standards.

Design smooth animations and transitions for AI response streaming.

Design data visualizations for AI metrics and model diagnostics.

Design multi-turn dialog systems with context and flow management.

Design error state UI patterns with retry, recovery, and fallback options.

Design forms for AI interactions with validation, accessibility, and feedback.

Create consistent icon systems for AI UI workflows and operations.

Design layout patterns for responsive AI dashboards and chat interfaces.

Design loading states and skeleton screens during AI processing.

Design onboarding flows for AI features with guided tours and prompts.

Ensure responsive design across devices for AI tools and dashboards.

Manage UI state transitions during multi-turn AI interactions.

Define design tokens for colors, spacing, typography in AI UIs.

Implement light/dark themes and custom branding for AI products.

Design reusable UI components for AI applications (buttons, cards, modals).

Implement deterministic agents with structured output and validation.

FAI Discovery — meta-plugin for exploring and recommending agents, instructions, skills, hooks.

Auto-generate API and architecture documentation from code annotations.

Apply Domain-Driven Design principles to AI system architecture.

Generate Draw.io diagrams from architecture definitions automatically.

Build dynamic prompts that adapt based on user context and history.

Generate test cases for edge cases in AI workflows.

Configure EditorConfig for consistent code style across team.

Choosing between embedding models (text-embedding-3-small vs large vs ada-002),Configuring dimensions, batch sizes, and chunking parameters,Benchmarking embeddi

Break down epics into architecture tasks and technical stories.

Break down epics into product management stories and features.

The essential FAI toolkit — WAF-aligned agents (security reviewer, cost optimizer, architect), cross-cutting instructions (OWASP, agent-safety.

Adopt evaluation-driven development for continuous AI quality assessment.

Run evaluation pipelines with metrics tracking and result reporting.

Evaluate Enterprise RAG recall, precision, and groundedness.

Evaluate Landing Zone compliance, security posture, and governance.

Evaluate Deterministic Agent output consistency and reliability.

Evaluate Voice AI latency, accuracy, and conversation quality.

Evaluate ticket resolution quality and automation effectiveness.

Evaluate OCR accuracy and entity extraction correctness.

Evaluate multi-agent coordination and task completion.

Evaluate bot conversation quality and user satisfaction.

Evaluate AI Search Portal search quality and reranking accuracy.

Evaluate Content Moderation coverage and policy adherence.

Evaluate Advanced Landing Zone resilience and performance.

Evaluate Model Serving latency, throughput, and availability.

Evaluate fine-tuning quality improvements and job success.

Evaluate gateway routing efficiency and cost savings.

Evaluate multi-modal document processing accuracy.

Evaluate extension adoption and user engagement metrics.

Evaluate observability coverage and alerting effectiveness.

Evaluate prompt versioning and A/B test performance.

Evaluate edge AI model performance and resource utilization on devices.

Evaluate anomaly detection accuracy and false-positive rates.

Evaluate agentic RAG decision quality and retrieval effectiveness.

Evaluate multi-agent swarm coordination and task completion.

Evaluate browser automation success rate and error recovery.

Build comprehensive evaluation frameworks for AI system quality gates.

Number of previous evaluations for moving average

Generate Excalidraw diagrams from architecture descriptions.

Design fabric lakehouses for unified data analytics and AI.

Scaffold FastAPI microservices with async handlers and OpenAPI.

Break down features into implementation tasks with acceptance criteria.

Finalize agent system prompts with guardrails and context anchoring.

Prepare and execute LLM fine-tuning with quality evaluation.

Craft opening prompts to gather requirements for AI systems.

Design workflows in Azure Flow Studio or Zapier.

Establish project folder structure for AI solution plays.

Ensure GDPR compliance in AI data processing and storage.

Use GitHub CLI for repository and issue automation.

Apply conventional commits and meaningful commit messages.

Implement Git Flow branching strategy for team collaboration.

Triage and prioritize GitHub issues using labels and automation.

Manage GitHub issues with automation, templates, and workflows.

Execute effective PR reviews with checklists and CI gates.

Define go-to-market strategy for AI products.

Build developer ecosystem and community engagement.

Design enterprise onboarding workflows for AI solutions.

Plan enterprise deployments with RFP responses.

Communicate AI value propositions to investors.

Execute go-to-market launch plan for AI product.

Establish operating cadence for AI product team.

Build partnership strategy for AI platform ecosystem.

Define product positioning and competitive differentiation.

Implement product-led growth strategy for AI tools.

Define safety guardrails and acceptable use policies.

Implement human-in-the-loop workflows for AI decisions.

Generate implementation plans from architecture.

Import existing infrastructure as code for modernization.

Optimize model inference latency and throughput.

Refactor Java code via extract method patterns.

Write Jest tests for JavaScript/TypeScript applications.

Write JUnit tests for Java applications with coverage.

Monthly check for stale FROOT knowledge modules — scores staleness across docs, plays, primitives, and schemas using a weighted multi-signal algorithm. Generate

Integrate LangChain with Azure OpenAI, semantic search, RAG chains, memory systems, and production tooling.

Generate LLMS.txt file from codebase structure to help LLMs understand repository context and conventions.

Load test an AI endpoint with k6/Locust for p95 latency and error rates

Guide through creating a complete, production-ready contribution to an open-source repository with testing, documentation, and review readiness.

|

Create or update fai-manifest.json with solution play context, primitive wiring, and guardrails thresholds.

Weekly marketplace integrity check — validates all plugin.json files, verifies referenced primitives exist, detects orphaned plugins, and regenerates marketplac

Scaffold a production-ready C#/.NET MCP server with ModelContextProtocol NuGet, dependency injection, async tools, and Azure Managed Identity.

|

|

|

|

|

Scaffold a production-ready Python MCP server with FastMCP decorators, async tools, structured outputs, and Azure integration.

Generate a project skeleton for Python MCP servers with FastMCP, async tools, testing harness, and Docker deployment.

Scaffold a Ruby MCP server using the official SDK with tool handlers, resource capabilities, and error handling.

Build a high-performance Rust MCP server with async tokio runtime, type-safe tool handlers, and zero-copy serialization.

Generate a Swift MCP server for macOS/iOS with type-safe tool definitions, Codable serialization, and native integration.

Generates Mermaid diagrams (flowcharts, sequence, Gantt) from natural language.

|

Implement model routing logic: cheap model for simple, capable for complex tasks

Generates optimized multi-stage Dockerfiles with minimal runtime images.

Create an observability dashboard with KQL queries for AI system health

Set up PII detection and masking with Azure AI Language service

Scaffold a new solution play with FAI Protocol wiring, directory structure, primitives stubs, and deployment config.

Aggregated portfolio assessment across all solution plays — dashboard of play health, WAF coverage, technology stack analysis, cost estimation, and ecosystem ma

Minimum passing grade (A-F)

Design Power BI dashboards with KPIs, drill-through navigation, real-time streaming, and row-level security.

Automated review of PRs that add or modify primitives — validates naming, frontmatter, schema, WAF alignment, duplicate detection, and file size. Posts structur

|

FAI Protocol Starter — quickstart for the FAI Protocol ecosystem. Scaffold fai-manifest.json, fai-context.json.

Create quality playbooks with test requirements, performance benchmarks, release criteria, and rollback procedures.

Test a RAG pipeline end-to-end with relevance and groundedness metrics

Set up RBAC role assignments for a solution play's Azure resources

|

|

|

|

Preview only — do not create issue

|

|

|

|

|

|

Implement semantic caching for AI responses with Redis and embedding similarity

|

|

Set up SLA monitoring with availability, latency, and quality metrics

|

|

|

|

|

|

Configure SSL certificates for custom domains on Azure App Service/AKS

Comma-separated play numbers to exempt (e.g., 01,02)

Implement streaming AI responses with Server-Sent Events (SSE)

Enforce structured JSON output from LLMs with schema validation

|

|

|

|

|

|

|

|

Enforce token budgets per user/team with tracking and alerting

|

|

|

|

Tune Play 05 (IT Ticket Resolution) classifier routing, priority scoring, SLA thresholds, and escalation model config.

|

Tune Play 07 (Multi-Agent Service) agent orchestration, handoff rules, model routing, and inter-agent communication config.

Tune Play 08 (Copilot Studio Bot) topic routing, generative answers config, handoff triggers, and channel settings.

Tune Play 09 (AI Search Portal) semantic ranking, scoring profiles, suggesters, and index schema for optimal relevance.

Tune Play 10 (Content Moderation) severity thresholds, category blocklists, Prompt Shields config, and review workflows.

Tune Play 11 (AI Landing Zone Advanced) hub-spoke topology, private DNS, governance policies, and network segmentation.

Tune Play 12 (Model Serving AKS) GPU node pools, vLLM configuration, autoscaling policies, and inference optimization.

Tune Play 13 (Fine-Tuning Workflow) training hyperparameters, dataset validation, LoRA config, and evaluation metrics.

Tune Play 14 (Cost-Optimized AI Gateway) model routing rules, token budgets, caching policies, and APIM rate limiting.

Tune Play 15 multi-modal document processing with OCR, vision model selection, extraction confidence, and fallback routing.

Tune Play 16 Teams extension behavior with command routing, intent matching, adaptive card payloads, and auth flow.

Tune Play 17 observability settings for traces, semantic metrics, alert thresholds, and log retention policy.

Tune Play 18 prompt management with version gates, A/B split, rollback policy, and template lint checks.

Tune Play 19 edge deployment for Phi-4 with quantization, device constraints, and offline fallback behavior.

Tune Play 20 anomaly detection with window sizing, seasonality handling, threshold calibration, and alert suppression.

Tune Play 21 agentic RAG with planner depth, retrieval fan-out, reranker policy, and citation strictness.

Tune Play 22 swarm behavior with role assignment, consensus thresholds, conflict policy, and budget controls.

Tune Play 23 browser automation with selector strategy, retry policy, anti-flake waits, and safety restrictions.

Generate production-ready tutorials with prerequisites, runnable code, verification steps, and troubleshooting paths.

Create and populate a vector search index in Azure AI Search or Cosmos DB

Per-PR WAF pillar validation — scans changed files for security anti-patterns, reliability gaps, cost waste, operational issues, performance bottlenecks, and re

Set up webhooks for AI system events: evaluation results, safety alerts, cost alerts

FastAPI standards — Pydantic models, dependency injection, async endpoints, and OpenAPI-first design.

Fine-tuning data standards — JSONL format, quality validation, class balance, edge case inclusion.

Fine-Tuning & MLOps — dataset curation, model training, hyperparameter optimization, model registry.

Fine-Tuning Workflow — dataset preparation, training job orchestration, evaluation pipelines, model registry.

Play 13 patterns — Fine-tuning patterns — JSONL data prep, LoRA config, eval metrics, A/B comparison, model versioning.

Flask standards — blueprints, app factory, SQLAlchemy, and production configuration patterns.

Frontend Web Development — React, Angular, Vue, Svelte, Astro, and Tailwind CSS patterns. Component architecture, state management, accessibility.

GenAI foundations coding — token counting, model parameter configuration, inference optimization.

GitHub Actions CI/CD standards — SHA-pinned actions, minimal permissions, secrets handling, and reusable workflows.

Go Development — high-performance services, gRPC APIs, concurrent patterns, and cloud-native tooling. Idiomatic Go with table-driven tests.

Go MCP server development — go-sdk/mcp, struct-based I/O, context handling.

Go MCP Development — build high-performance MCP servers in Go with goroutine concurrency, gRPC transport, and minimal memory footprint for edge deployment.

Go coding standards — idiomatic Go, return early, error handling, goroutines, and minimal dependency patterns.

GPU infrastructure standards — VRAM sizing, quantization selection, serving framework config, scaling rules.

GraphQL standards — schema design, resolvers, DataLoader, error handling.

gRPC standards — protobuf design, streaming, error codes, health checking.

HTML/CSS standards — semantic HTML, accessibility, 60-30-10 color rule, and responsive design.

Incident Response — on-call triage, KQL query generation, Azure resource diagnostics, runbook automation.

IT Ticket Resolution — automated incident classification, knowledge base search, resolution suggestion.

Play 05 patterns — IT ticket patterns — intent classification, knowledge base search, automated resolution, escalation rules.

Java Development — Spring Boot, Quarkus, JUnit 5, Gradle/Maven builds, and microservice patterns. Enterprise Java with reactive streams.

Java MCP server development — official SDK, reactive streams, Spring Boot integration.

Java MCP Development — build MCP servers in Java with Spring Boot, reactive streams, Maven/Gradle builds, and enterprise middleware integration.

Java coding standards — constructor injection, immutable objects, streams API, JUnit 5, and Spring Boot patterns.

Kotlin MCP server development — coroutines, data classes, Ktor, and Gradle patterns.

Kotlin MCP Development — build MCP servers in Kotlin with Ktor, coroutines, multiplatform support, and Android-compatible tool implementations.

Kotlin coding standards — coroutines, data classes, null safety, extension functions, and Gradle build patterns.

Kubernetes Orchestration — cluster setup, Helm charts, KEDA autoscaling, Dapr sidecars, Istio service mesh.

Kubernetes standards — pod security, resource limits, health probes, and production deployment patterns.

Laravel standards — Eloquent, Blade, Artisan, queue workers, and security.

LLM selection standards — model routing config, benchmark-driven selection, cost/quality tradeoffs.

LLM Observability — trace every LLM call with input/output logging, token counts, latency percentiles, cost attribution.

Localization standards — i18n key management, RTL support, pluralization, date/number formatting.

Markdown standards — CommonMark, GFM, accessibility, heading hierarchy, and structured documentation.

MAUI standards — cross-platform, MVVM, dependency injection, platform-specific.

MCP integration patterns — tool description quality, parameter design, error handling, transport selection.

Persistent project documentation standards — maintain context across AI sessions with structured memory files.

ASP.NET Minimal API standards — endpoint routing, DI, filters, OpenAPI, rate limiting.

Mobile Development — Swift/SwiftUI for iOS, Kotlin for Android, .NET MAUI for cross-platform.

Model Serving on AKS — GPU-accelerated inference, autoscaling with KEDA, model versioning, A/B deployment.

Play 12 patterns — Model serving patterns — vLLM config, GPU scheduling, health probes, autoscaling, quantization selection.

MongoDB standards — schema design, indexes, aggregation pipelines, and Atlas Vector Search patterns.

Multi-Agent Service — orchestrated agent teams with supervisor patterns, tool delegation, shared memory.

Play 07 patterns — Multi-agent patterns — supervisor routing, turn limits, token budgets, cross-agent context passing.

Deploy specialized AI agents that collaborate via supervisor, pipeline, and debate patterns — .

Play 22 patterns — Swarm patterns — supervisor delegation, specialist budgets, turn management, result synthesis.

Multi-Modal Document Processing — combine OCR, vision, speech, and text analysis for complex document workflows. Extract structured data from PDFs.

Play 15 patterns — Multi-modal patterns — GPT-4o Vision, image+text pipelines, PDF rendering, chart interpretation.

NestJS standards — DI, decorators, modular architecture, Pipes validation, and TypeORM patterns.

Next.js 16 App Router standards — Server Components by default, streaming with Suspense, Turbopack, Tailwind v4, static export for FAI.dev, and production optim

No heredoc in terminal — prevent terminal file corruption from heredoc syntax in AI-generated commands.

Nuxt 3 standards — Vue 3, SSR, auto-imports, and composable patterns.

Object calisthenics standards — 9 rules for clean, maintainable code across OOP languages.

OpenAPI standards — spec-first design, versioning, security schemes, examples.

GitHub Actions operational excellence — reusable workflows, matrix testing, artifact management.

Monitoring standards — Application Insights, structured logging, custom metrics, alert thresholds.

Oracle Migration — Oracle-to-PostgreSQL and Oracle-to-Azure SQL migration patterns. Schema conversion, PL/SQL translation, data pipeline design.

Power Apps Component Framework standards — lifecycle methods, React integration, and TypeScript patterns.

Performance optimization standards — measure first, profile before optimizing, and avoid premature optimization.

Python performance — async/await, connection pooling, streaming, profiling with cProfile/py-spy.

TypeScript performance — event loop, streaming SSE, connection pooling, memory profiling.

Pester 5 testing standards — Describe/It blocks, TestDrive, and PowerShell module testing patterns.

PHP MCP server development — attributes, typed properties, Composer.

PHP MCP Development — build MCP servers in PHP with Laravel integration, Composer packaging, Swoole async runtime, and WordPress compatibility.

PHP coding standards — typed properties, attributes, PSR-12, Composer, and modern PHP 8.3+ patterns.

Interactive slash command to assess whether a solution play is still relevant — checks Azure service availability, pricing changes, SDK deprecations, and altern

Playwright testing standards — role-based locators, auto-wait, visual regression, and accessibility testing.

Power Apps Canvas standards — delegation, collections, component libraries.

Power Apps Model-driven standards — forms, views, business rules, Dataverse security.

Power Automate flow standards — error handling, parallel branches, approvals, SLA tracking.

Power BI Analytics — DAX formulas, data modeling, report design, dashboard layout.

Power BI DAX standards — CALCULATE patterns, time intelligence, performance optimization.

Power Pages standards — Liquid templates, web forms, entity permissions, progressive profiles.

Power Platform AI integration — Power Apps code components, Power BI DAX and modeling, Power Automate flow design, Dataverse SDK patterns.

Custom connector standards — OpenAPI definition, auth configuration, throttling, testing.

PowerShell standards — Verb-Noun naming, PascalCase, standard parameters, and error handling patterns.

Prisma ORM standards — schema design, migrations, query optimization, relation loading, type safety.

Production deployment standards — blue-green, canary rollout, health probes, rollback criteria.

Project Planning — PRDs, epic breakdown, implementation plans, technical spikes.

Prompt engineering standards — system message structure, few-shot patterns, output format enforcement.

Prompt Engineering — chain-of-thought, few-shot, tree-of-thought, and meta-prompting patterns. Template management, dynamic prompt assembly.

Prompt Management — version-controlled prompt templates, A/B testing, evaluation pipelines.

Play 18 patterns — Prompt management patterns — version control, A/B testing, template variables, prompt libraries.

Pydantic standards — model design, validation, serialization, settings management, custom validators.

pytest testing standards — fixtures, parametrize, coverage, and mock patterns for Python.

Python Full-Stack — FastAPI, Django, Flask, Pydantic, SQLAlchemy, pytest, and async patterns. Data science to web APIs with type safety.

Python MCP server development standards — FastMCP patterns, @mcp.tool() decorators, Pydantic parameter types, async handlers, resource definitions, and producti

Python MCP Development — build MCP servers in Python with FastMCP, asyncio, Pydantic models, type-safe tool schemas, and Azure Functions hosting.

Python coding standards aligned with Azure Well-Architected Framework pillars — secure credential handling, async patterns, structured error handling, cost-awar

Quarkus standards — Java 21, CDI, reactive, native compilation patterns.

R coding standards — vectorized operations, tidyverse, lower_snake_case, and reproducible analysis patterns.

RAG coding standards — chunking config, embedding batch calls, reranker integration, citation injection.

Responsible AI bias testing — disaggregated metrics, diverse evaluation datasets, fairness benchmarks.

Responsible AI content safety — Azure Content Safety integration, filter thresholds, PII redaction.

Ruby on Rails standards — MVC conventions, Active Record, migrations, and RuboCop enforcement.

C# reliability standards — Polly retry/circuit breaker, health checks, exception handling, resilience.

Python reliability standards — retry with tenacity, circuit breakers, health checks, structured logging.

TypeScript reliability standards — AbortSignal timeout, retry patterns, health endpoints, error boundaries.

Responsible AI — content safety, bias testing, fairness metrics, transparency cards.

Responsible AI coding — content safety integration, red team test coverage, bias metric collection.

Ruby MCP server development — mcp gem, block DSL, Rails integration.

Ruby MCP Development — build MCP servers in Ruby with Rails integration, Rack middleware, Sorbet typing, and Bundler gem packaging.

Ruby coding standards — Ruby 3.3+, RuboCop enforcement, Ractor patterns, and Rails conventions.

Rust Development — systems programming, zero-cost abstractions, async with Tokio, WASM targets.

Rust MCP server development — rmcp SDK, tokio, proc macros, serde, and high-performance tool serving.

Rust MCP Development — build blazing-fast MCP servers in Rust with Tokio async runtime, RMCP SDK, WASM compilation, and zero-allocation tool handlers.

Rust coding standards — ownership, lifetimes, ResultT,E, serde, tokio async, and memory safety patterns.

Salesforce Apex standards — bulkification, governor limits, trigger patterns, and testing.

Salesforce Integration — Apex development, Lightning Web Components, SOQL optimization, Salesforce MCP connectors.

Salesforce Lightning Web Components standards — reactive properties, wire adapters, and accessibility.

Scala coding standards — immutability, val over var, pattern matching, and functional programming patterns.

Bicep security standards — @secure() parameters, private endpoints, Managed Identity, diagnostic settings.

C# security standards — parameterized queries, output encoding, anti-forgery tokens, secure headers.

Security Hardening — OWASP Top 10, secrets scanning, dependency auditing, supply chain security, threat modeling.

Comprehensive OWASP security standards for all code — covers Top 10 vulnerabilities, LLM-specific security (OWASP Top 10 for LLMs), input validation, output enc

Python security standards — input validation, secrets handling, dependency scanning, SQL injection prevention.

TypeScript security standards — XSS prevention, CSP headers, input sanitization, dependency audit.

Self-documenting code standards — comment WHY not WHAT, meaningful names, and code as documentation.

Semantic Kernel standards — kernel config, plugin design, filter pipeline, memory store integration.

Shell scripting standards — set -euo pipefail, safe expansions, quoting, and portable POSIX patterns.

SignalR real-time standards — hub design, groups, streaming, connection management, Azure SignalR Service.

Spring Boot standards — constructor injection, profiles, YAML config, and production patterns.

SQL optimization standards — index strategy, query plans, normalized design, and migration patterns.

SQLAlchemy standards — async sessions, relationship mapping, migration with Alembic, connection pooling.

Svelte 5 standards — runes, SvelteKit, TypeScript, and minimal-bundle patterns.

Swift MCP server development — actors, Codable, async/await patterns.

Swift MCP Development — build MCP servers in Swift with Vapor framework, SwiftUI tool previews, iOS/macOS native integration.

Swift coding standards — actors for concurrency, Codable, async/await, SwiftUI, and value types over reference types.

Tailwind CSS v4 standards — utility-first, component extraction, responsive design, and dark mode patterns.

Taming Copilot — prevent overreach, enforce constraints, verify before executing, undo patterns.

Technical Documentation — API references, architecture guides, README generation, changelog automation, tutorials.

Terraform Azure standards — AVM modules, CALMS framework, modular design.

Terraform IaC — module authoring, state management, workspace strategies, provider configuration.

Terraform standards — latest providers, modular design, state safety, and secrets management.

AI-powered testing — unit test generation, integration testing, E2E with Playwright, AI evaluation pipelines.

Polyglot testing standards — unit, integration, and E2E testing patterns for AI applications. Covers pytest, Vitest, xUnit, Playwright, mock strategies for LLM

tRPC standards — router design, middleware, error handling, type-safe API calls, input validation.

TypeScript Full-Stack — Next.js, React, NestJS, Prisma, Zod, Vitest, and end-to-end type safety. Modern web development with server components.

TypeScript MCP server development standards — @modelcontextprotocol/sdk patterns, Zod parameter schemas, McpServer class, stdio/SSE transports, and npm publishi

TypeScript MCP Development — build MCP servers in TypeScript with Node.js, Express/Fastify hosting, Zod schema validation, and npm package distribution.

TypeScript/JavaScript coding standards aligned with Azure WAF pillars — secure credential handling, async patterns, Zod validation, structured error handling, a

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

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

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

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

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

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

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