diff --git a/docs/README.skills.md b/docs/README.skills.md index 5dda6101..26affb64 100644 --- a/docs/README.skills.md +++ b/docs/README.skills.md @@ -52,7 +52,7 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-skills) for guidelines on how to | [autoresearch](../skills/autoresearch/SKILL.md) | Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric. | None | | [aws-cdk-python-setup](../skills/aws-cdk-python-setup/SKILL.md) | Setup and initialization guide for developing AWS CDK (Cloud Development Kit) applications in Python. This skill enables users to configure environment prerequisites, create new CDK projects, manage dependencies, and deploy to AWS. | None | | [az-cost-optimize](../skills/az-cost-optimize/SKILL.md) | Analyze Azure resources used in the app (IaC files and/or resources in a target rg) and optimize costs - creating GitHub issues for identified optimizations. | None | -| [azure-architecture-autopilot](../skills/azure-architecture-autopilot/SKILL.md) | Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep.
When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services | `.gitignore`
`README.md`
`assets/06-architecture-diagram.png`
`assets/07-azure-portal-resources.png`
`assets/08-deployment-succeeded.png`
`references/ai-data.md`
`references/architecture-guidance-sources.md`
`references/azure-common-patterns.md`
`references/azure-dynamic-sources.md`
`references/bicep-generator.md`
`references/bicep-reviewer.md`
`references/phase0-scanner.md`
`references/phase1-advisor.md`
`references/phase4-deployer.md`
`references/service-gotchas.md`
`scripts/cli.py`
`scripts/generator.py`
`scripts/icons.py` | +| [azure-architecture-autopilot](../skills/azure-architecture-autopilot/SKILL.md) | Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep.
When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services | `.gitignore`
`assets/06-architecture-diagram.png`
`assets/07-azure-portal-resources.png`
`assets/08-deployment-succeeded.png`
`references/ai-data.md`
`references/architecture-guidance-sources.md`
`references/azure-common-patterns.md`
`references/azure-dynamic-sources.md`
`references/bicep-generator.md`
`references/bicep-reviewer.md`
`references/phase0-scanner.md`
`references/phase1-advisor.md`
`references/phase4-deployer.md`
`references/service-gotchas.md`
`scripts/cli.py`
`scripts/generator.py`
`scripts/icons.py` | | [azure-deployment-preflight](../skills/azure-deployment-preflight/SKILL.md) | Performs comprehensive preflight validation of Bicep deployments to Azure, including template syntax validation, what-if analysis, and permission checks. Use this skill before any deployment to Azure to preview changes, identify potential issues, and ensure the deployment will succeed. Activate when users mention deploying to Azure, validating Bicep files, checking deployment permissions, previewing infrastructure changes, running what-if, or preparing for azd provision. | `references/ERROR-HANDLING.md`
`references/REPORT-TEMPLATE.md`
`references/VALIDATION-COMMANDS.md` | | [azure-devops-cli](../skills/azure-devops-cli/SKILL.md) | Manage Azure DevOps resources via CLI including projects, repos, pipelines, builds, pull requests, work items, artifacts, and service endpoints. Use when working with Azure DevOps, az commands, devops automation, CI/CD, or when user mentions Azure DevOps CLI. | `references/advanced-usage.md`
`references/boards-and-iterations.md`
`references/org-and-security.md`
`references/pipelines-and-builds.md`
`references/repos-and-prs.md`
`references/variables-and-agents.md`
`references/workflows-and-patterns.md` | | [azure-pricing](../skills/azure-pricing/SKILL.md) | Fetches real-time Azure retail pricing using the Azure Retail Prices API (prices.azure.com) and estimates Copilot Studio agent credit consumption. Use when the user asks about the cost of any Azure service, wants to compare SKU prices, needs pricing data for a cost estimate, mentions Azure pricing, Azure costs, Azure billing, or asks about Copilot Studio pricing, Copilot Credits, or agent usage estimation. Covers compute, storage, networking, databases, AI, Copilot Studio, and all other Azure service families. | `references/COPILOT-STUDIO-RATES.md`
`references/COST-ESTIMATOR.md`
`references/REGIONS.md`
`references/SERVICE-NAMES.md` | @@ -225,7 +225,7 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-skills) for guidelines on how to | [penpot-uiux-design](../skills/penpot-uiux-design/SKILL.md) | Comprehensive guide for creating professional UI/UX designs in Penpot using MCP tools. Use this skill when: (1) Creating new UI/UX designs for web, mobile, or desktop applications, (2) Building design systems with components and tokens, (3) Designing dashboards, forms, navigation, or landing pages, (4) Applying accessibility standards and best practices, (5) Following platform guidelines (iOS, Android, Material Design), (6) Reviewing or improving existing Penpot designs for usability. Triggers: "design a UI", "create interface", "build layout", "design dashboard", "create form", "design landing page", "make it accessible", "design system", "component library". | `references/accessibility.md`
`references/component-patterns.md`
`references/platform-guidelines.md`
`references/setup-troubleshooting.md` | | [phoenix-cli](../skills/phoenix-cli/SKILL.md) | Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, review experiments, inspect datasets, and query the GraphQL API. Use when debugging AI/LLM applications, analyzing trace data, working with Phoenix observability, or investigating LLM performance issues. | None | | [phoenix-evals](../skills/phoenix-evals/SKILL.md) | Build and run evaluators for AI/LLM applications using Phoenix. | `references/axial-coding.md`
`references/common-mistakes-python.md`
`references/error-analysis-multi-turn.md`
`references/error-analysis.md`
`references/evaluate-dataframe-python.md`
`references/evaluators-code-python.md`
`references/evaluators-code-typescript.md`
`references/evaluators-custom-templates.md`
`references/evaluators-llm-python.md`
`references/evaluators-llm-typescript.md`
`references/evaluators-overview.md`
`references/evaluators-pre-built.md`
`references/evaluators-rag.md`
`references/experiments-datasets-python.md`
`references/experiments-datasets-typescript.md`
`references/experiments-overview.md`
`references/experiments-running-python.md`
`references/experiments-running-typescript.md`
`references/experiments-synthetic-python.md`
`references/experiments-synthetic-typescript.md`
`references/fundamentals-anti-patterns.md`
`references/fundamentals-model-selection.md`
`references/fundamentals.md`
`references/observe-sampling-python.md`
`references/observe-sampling-typescript.md`
`references/observe-tracing-setup.md`
`references/production-continuous.md`
`references/production-guardrails.md`
`references/production-overview.md`
`references/setup-python.md`
`references/setup-typescript.md`
`references/validation-evaluators-python.md`
`references/validation-evaluators-typescript.md`
`references/validation.md` | -| [phoenix-tracing](../skills/phoenix-tracing/SKILL.md) | OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production. | `README.md`
`references/annotations-overview.md`
`references/annotations-python.md`
`references/annotations-typescript.md`
`references/fundamentals-flattening.md`
`references/fundamentals-overview.md`
`references/fundamentals-required-attributes.md`
`references/fundamentals-universal-attributes.md`
`references/instrumentation-auto-python.md`
`references/instrumentation-auto-typescript.md`
`references/instrumentation-manual-python.md`
`references/instrumentation-manual-typescript.md`
`references/metadata-python.md`
`references/metadata-typescript.md`
`references/production-python.md`
`references/production-typescript.md`
`references/projects-python.md`
`references/projects-typescript.md`
`references/sessions-python.md`
`references/sessions-typescript.md`
`references/setup-python.md`
`references/setup-typescript.md`
`references/span-agent.md`
`references/span-chain.md`
`references/span-embedding.md`
`references/span-evaluator.md`
`references/span-guardrail.md`
`references/span-llm.md`
`references/span-reranker.md`
`references/span-retriever.md`
`references/span-tool.md` | +| [phoenix-tracing](../skills/phoenix-tracing/SKILL.md) | OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production. | `references/annotations-overview.md`
`references/annotations-python.md`
`references/annotations-typescript.md`
`references/fundamentals-flattening.md`
`references/fundamentals-overview.md`
`references/fundamentals-required-attributes.md`
`references/fundamentals-universal-attributes.md`
`references/instrumentation-auto-python.md`
`references/instrumentation-auto-typescript.md`
`references/instrumentation-manual-python.md`
`references/instrumentation-manual-typescript.md`
`references/metadata-python.md`
`references/metadata-typescript.md`
`references/production-python.md`
`references/production-typescript.md`
`references/projects-python.md`
`references/projects-typescript.md`
`references/sessions-python.md`
`references/sessions-typescript.md`
`references/setup-python.md`
`references/setup-typescript.md`
`references/span-agent.md`
`references/span-chain.md`
`references/span-embedding.md`
`references/span-evaluator.md`
`references/span-guardrail.md`
`references/span-llm.md`
`references/span-reranker.md`
`references/span-retriever.md`
`references/span-tool.md` | | [php-mcp-server-generator](../skills/php-mcp-server-generator/SKILL.md) | Generate a complete PHP Model Context Protocol server project with tools, resources, prompts, and tests using the official PHP SDK | None | | [planning-oracle-to-postgres-migration-integration-testing](../skills/planning-oracle-to-postgres-migration-integration-testing/SKILL.md) | Creates an integration testing plan for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Analyzes a single project to identify repositories, DAOs, and service layers that interact with the database, then produces a structured testing plan. Use when planning integration test coverage for a migrated project, identifying which data access methods need tests, or preparing for Oracle-to-PostgreSQL migration validation. | None | | [plantuml-ascii](../skills/plantuml-ascii/SKILL.md) | Generate ASCII art diagrams using PlantUML text mode. Use when user asks to create ASCII diagrams, text-based diagrams, terminal-friendly diagrams, or mentions plantuml ascii, text diagram, ascii art diagram. Supports: Converting PlantUML diagrams to ASCII art, Creating sequence diagrams, class diagrams, flowcharts in ASCII format, Generating Unicode-enhanced ASCII art with -utxt flag | None | diff --git a/skills/azure-architecture-autopilot/README.md b/skills/azure-architecture-autopilot/README.md deleted file mode 100644 index 734638b9..00000000 --- a/skills/azure-architecture-autopilot/README.md +++ /dev/null @@ -1,188 +0,0 @@ -

Azure Architecture Autopilot

- -

- Design → Diagram → Bicep → Deploy — all from natural language -

- -

- Copilot Skill - Azure - Bicep - Service Types - License -

- -

- Azure Architecture Autopilot designs Azure infrastructure from natural language,
- generates interactive diagrams, produces modular Bicep templates, and deploys — all through conversation.
- It also scans existing resources, visualizes them as architecture diagrams, and refines them on the fly. -

- - -

- Interactive Azure architecture diagram with 605+ official icons -

- -

- ↑ Auto-generated interactive diagram — drag, zoom, click for details, export to PNG -

- -

- Deployment succeeded -    - Azure Portal — deployed resources -

- -

- ↑ Real Azure resources deployed from the generated Bicep templates -

- -

- How It Works • - Features • - Prerequisites • - Usage • - Architecture -

- ---- - -## 🔄 How It Works - -``` -Path A: "Build me a RAG chatbot on Azure" - ↓ - 🎨 Design → 🔧 Bicep → ✅ Review → 🚀 Deploy - -Path B: "Analyze my current Azure resources" - ↓ - 🔍 Scan → 🎨 Modify → 🔧 Bicep → ✅ Review → 🚀 Deploy -``` - -| Phase | Role | What Happens | -|:-----:|------|--------------| -| **0** | 🔍 Scanner | Scans existing Azure resources via `az` CLI → auto-generates architecture diagram | -| **1** | 🎨 Advisor | Interactive design through conversation — asks targeted questions with smart defaults | -| **2** | 🔧 Generator | Produces modular Bicep: `main.bicep` + `modules/*.bicep` + `.bicepparam` | -| **3** | ✅ Reviewer | Compiles with `az bicep build`, checks security & best practices | -| **4** | 🚀 Deployer | `validate` → `what-if` → preview diagram → `create` (5-step mandatory sequence) | - ---- - -## ✨ Features - -| | Feature | Description | -|---|---------|-------------| -| 📦 | **Zero Dependencies** | 605+ Azure icons bundled — no `pip install`, works offline | -| 🎨 | **Interactive Diagrams** | Drag-and-drop HTML with zoom, click details, PNG export | -| 🔍 | **Resource Scanning** | Analyze existing Azure infra → auto-generate architecture diagrams | -| 💬 | **Natural Language** | *"It's slow"*, *"reduce costs"*, *"add security"* → guided resolution | -| 📊 | **Live Verification** | API versions, SKUs, model availability fetched from MS Docs in real-time | -| 🔒 | **Secure by Default** | Private Endpoints, RBAC, managed identity — no secrets in files | -| ⚡ | **Parallel Preload** | Next-phase info loaded while waiting for user input | -| 🌐 | **Multi-Language** | Auto-detects user language — responds in English, Korean, or any language | - ---- - -## ⚙️ Prerequisites - -| Tool | Required | Install | -|------|:--------:|---------| -| **GitHub Copilot CLI** | ✅ | [Install guide](https://docs.github.com/copilot/concepts/agents/about-copilot-cli) | -| **Azure CLI** | ✅ | `winget install Microsoft.AzureCLI` / `brew install azure-cli` | -| **Python 3.10+** | ✅ | `winget install Python.Python.3.12` / `brew install python` | - -> No additional packages required — the diagram engine is bundled in `scripts/`. - -### 🤖 Recommended Models - -| | Models | Notes | -|---|--------|-------| -| 🏆 **Best** | Claude Opus 4.5 / 4.6 | Most reliable for all 5 phases | -| ✅ **Recommended** | Claude Sonnet 4.5 / 4.6 | Best cost-performance balance | -| ⚠️ **Minimum** | Claude Sonnet 4, GPT-5.1+ | May skip steps in complex architectures | - ---- - -## 🚀 Usage - -### Path A — Build new infrastructure - -``` -"Build a RAG chatbot with Foundry and AI Search" -"Create a data platform with Databricks and ADLS Gen2" -"Deploy Fabric + ADF pipeline with private endpoints" -"Set up a microservices architecture with AKS and Cosmos DB" -``` - -### Path B — Analyze & modify existing resources - -``` -"Analyze my current Azure infrastructure" -"Scan rg-production and show me the architecture" -"What resources are in my subscription?" -``` - -Then modify through conversation: -``` -"Add 3 VMs to this architecture" -"The Foundry endpoint is slow — what can I do?" -"Reduce costs — downgrade AI Search to Basic" -"Add private endpoints to all services" -``` - -### 📂 Output Structure - -``` -/ -├── 00_arch_current.html ← Scanned architecture (Path B) -├── 01_arch_diagram_draft.html ← Design diagram -├── 02_arch_diagram_preview.html ← What-if preview -├── 03_arch_diagram_result.html ← Deployment result -├── main.bicep ← Orchestration -├── main.bicepparam ← Parameter values -└── modules/ - └── *.bicep ← Per-service modules -``` - ---- - -## 📁 Architecture - -``` -SKILL.md ← Lightweight router (~170 lines) -│ -├── scripts/ ← Embedded diagram engine -│ ├── generator.py ← Interactive HTML generator -│ ├── icons.py ← 605+ Azure icons (Base64 SVG) -│ └── cli.py ← CLI entry point -│ -└── references/ ← Phase instructions + patterns - ├── phase0-scanner.md ← 🔍 Resource scanning - ├── phase1-advisor.md ← 🎨 Architecture design - ├── bicep-generator.md ← 🔧 Bicep generation - ├── bicep-reviewer.md ← ✅ Code review - ├── phase4-deployer.md ← 🚀 Deployment pipeline - ├── service-gotchas.md ← Required properties & PE mappings - ├── azure-common-patterns.md ← Security & naming patterns - ├── azure-dynamic-sources.md ← MS Docs URL registry - ├── architecture-guidance-sources.md - └── ai-data.md ← AI/Data service domain pack -``` - -> **Self-contained** — `SKILL.md` is a lightweight router. All phase logic lives in `references/`. The diagram engine is embedded in `scripts/` with no external dependencies. - ---- - -## 📊 Supported Services (70+ types) - -All Azure services supported. AI/Data services have optimized templates; others are auto-looked up from MS Docs. - -**Key types:** `ai_foundry` · `openai` · `ai_search` · `storage` · `adls` · `keyvault` · `fabric` · `databricks` · `aks` · `vm` · `app_service` · `function_app` · `cosmos_db` · `sql_server` · `postgresql` · `mysql` · `synapse` · `adf` · `apim` · `service_bus` · `logic_apps` · `event_grid` · `event_hub` · `container_apps` · `app_insights` · `log_analytics` · `firewall` · `front_door` · `load_balancer` · `expressroute` · `sentinel` · `redis` · `iot_hub` · `digital_twins` · `signalr` · `acr` · `bastion` · `vpn_gateway` · `data_explorer` · `document_intelligence` ... - - ---- - -## 📄 License - -MIT © [Jeonghoon Lee](https://github.com/whoniiii) diff --git a/skills/phoenix-tracing/README.md b/skills/phoenix-tracing/README.md deleted file mode 100644 index 29065946..00000000 --- a/skills/phoenix-tracing/README.md +++ /dev/null @@ -1,24 +0,0 @@ -# Phoenix Tracing Skill - -OpenInference semantic conventions and instrumentation guides for Phoenix. - -## Usage - -Start with `SKILL.md` for the index and quick reference. - -## File Organization - -All files in flat `rules/` directory with semantic prefixes: - -- `span-*` - Span kinds (LLM, CHAIN, TOOL, etc.) -- `setup-*`, `instrumentation-*` - Getting started guides -- `fundamentals-*`, `attributes-*` - Reference docs -- `annotations-*`, `export-*` - Advanced features - -## Reference - -- [OpenInference Spec](https://github.com/Arize-ai/openinference/tree/main/spec) -- [Phoenix Documentation](https://docs.arize.com/phoenix) -- [Python OTEL API](https://arize-phoenix.readthedocs.io/projects/otel/en/latest/) -- [Python Client API](https://arize-phoenix.readthedocs.io/projects/client/en/latest/) -- [TypeScript API](https://arize-ai.github.io/phoenix/)