.github/skills/frontend-design-review/SKILL.md
Review and create distinctive, production-grade frontend interfaces with high design quality and design system compliance. Evaluates using three pillars: frictionless insight-to-action, quality craft, and trustworthy building. USE FOR: PR reviews, design reviews, accessibility audits, design system compliance checks, creative frontend design, UI code review, component reviews, responsive design checks, theme testing, and creating memorable UI. DO NOT USE FOR: Backend API reviews, database schema reviews, infrastructure or DevOps work, pure business logic without UI, or non-frontend code.
npx skillsauth add microsoft/skills frontend-design-reviewInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Review UI implementations against design quality standards and your design system OR create distinctive, production-grade frontend interfaces from scratch.
Evaluate existing UI for design system compliance, three quality pillars (Frictionless, Quality Craft, Trustworthy), accessibility, and code quality.
Create distinctive interfaces that avoid generic "AI slop" aesthetics, have clear conceptual direction, and execute with precision.
Before coding, commit to an aesthetic direction:
AVOID: Overused fonts, cliched color schemes, predictable layouts, cookie-cutter design without context-specific character.
Match implementation complexity to vision. Maximalist = elaborate code. Minimalist = restraint and precision.
Before implementing:
During review:
If component doesn't exist:
Evaluate: Task completable in ≤3 interactions? Primary action obvious and singular?
Red flags: Excessive clicks, multiple competing primary buttons, buried actions, dead ends.
Evaluate:
Red flags: Generic AI aesthetics, hardcoded values, implementation doesn't match Figma, broken reflow, missing focus indicators.
Evaluate:
Red flags: Missing AI disclaimers, opaque errors without guidance.
See references/review-output-format.md for the full review template.
See references/review-type-modifiers.md for context-specific review focus areas (PR, Creative, Design, Accessibility).
See references/quick-checklist.md for the pre-approval checklist covering design system compliance, aesthetic quality, frictionless, quality craft, and trustworthy pillars.
See references/pattern-examples.md for good/bad examples of creative frontend and design system review work.
Creative frontend principles inspired by Anthropic's frontend-design skill. Design review principles and quality pillar framework created by @Quirinevwm for systematic UI evaluation.
tools
KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.
development
Deploy, evaluate, and manage Foundry agents end-to-end: Docker build, ACR push, hosted/prompt agent create, container start, batch eval, prompt optimization, prompt optimizer workflows, agent.yaml, dataset curation from traces. USE FOR: deploy agent to Foundry, hosted agent, create agent, invoke agent, evaluate agent, run batch eval, optimize prompt, improve prompt, prompt optimization, prompt optimizer, improve agent instructions, optimize agent instructions, optimize system prompt, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, create dataset from traces, dataset versioning, eval trending, create AI Services, Cognitive Services, create Foundry resource, provision resource, knowledge index, agent monitoring, customize deployment, onboard, availability. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
testing
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.
testing
Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: "check quotas", "service limits", "current usage", "request quota increase", "quota exceeded", "validate capacity", "regional availability", "provisioning limits", "vCPU limit", "how many vCPUs available in my subscription".