This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
中文简介正在准备中。当前显示原文说明。
Design, review, and validate Azure cloud architectures. Use when choosing Azure compute, storage, networking, or identity services, or applying the Azure Well-Architected Framework to a workload.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
End-to-end Azure-specific architecture: service selection, Well-Architected Framework assessment, identity and networking patterns, cost optimization, and operational defaults. Provider-specific complement to our generic senior-cloud-architect skill — that one covers cross-cloud patterns; this one knows AKS pricing tiers, when to pick Cosmos over SQL DB, and how Front Door differs from Application Gateway.
| Situation | Skill applies |
|---|---|
| Designing an Azure architecture from scratch | Yes — start with the compute decision tree |
| Reviewing an existing Azure architecture | Yes — run WAF assessment via scripts/azure_waf_scorer.py |
| Validating an ARM/Bicep/Terraform plan | Yes — scripts/azure_architecture_validator.py |
| Estimating Azure cost for a workload | Yes — scripts/azure_cost_estimator.py |
| Picking compute, data store, networking, or identity | Yes — see the decision-trees reference |
| Going to production without WAF review | Don't — run the WAF scorer first |
Before designing or assessing, confirm these inputs. If any is unknown or vague, ASK — do not assume:
azure_architecture_validator.py vs azure_cost_estimator.py vs azure_waf_scorer.py)Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
| Tool | Purpose | Command |
|---|---|---|
azure_architecture_validator.py | Validate a Bicep/ARM/YAML workload for anti-patterns and missing best-practice settings | python scripts/azure_architecture_validator.py --bicep ./infra/*.bicep |
azure_cost_estimator.py | Estimate monthly Azure cost from a YAML workload spec | python scripts/azure_cost_estimator.py --workload-config workload.yaml |
azure_waf_scorer.py | Score a workload against the five Well-Architected pillars | python scripts/azure_waf_scorer.py --workload-config workload.yaml |
All scripts: stdlib only, argparse CLI, JSON or markdown output (--format).
Load the reference that matches the task — keep this file lean and pull detail on demand:
engineering/senior-cloud-architect — generic multi-cloud architecture patternsengineering/aws-solution-architect — AWS counterpartengineering/gcp-cloud-architect — GCP counterpartengineering/kubernetes-operator — for AKS operator-pattern workloadsra-qm-team/information-security-manager-iso27001 — for compliance-mapped controls (Azure has built-in Defender / Compliance Manager)ra-qm-team/soc2-compliance-expert — Azure-specific SOC 2 evidence collection还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
中文简介正在准备中。当前显示原文说明。
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
中文简介正在准备中。当前显示原文说明。
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
中文简介正在准备中。当前显示原文说明。
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
中文简介正在准备中。当前显示原文说明。
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
中文简介正在准备中。当前显示原文说明。
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
中文简介正在准备中。当前显示原文说明。