End-to-end orchestrator: from a business idea, app idea, or existing app to running Azure deployment with cost estimates and pre-deploy approval. Analyzes your app, auto-detects the right Azure services, scaffolds infrastructure code, and deploys — tailored to your app, not a template. Handles moving existing apps to Azure without rewriting or with minimal changes. WHEN: bring your app to Azure, plan my app, cost to run, is my code ready to deploy, deploy my app to the cloud, deploy all my services, what Azure services do I need, plan my Azure deployment, deploy my new app to Azure, one-click deploy, I have an app and want it on Azure, migrate my app to Azure, help me get started, build an app, no code yet, starter project. DO NOT USE FOR: running azd up (use azure-deploy), optimizing existing costs (use azure-cost), code readiness checks only (use azure-app-onboard-prereq).
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실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
⛔ Every repo goes through the full pipeline (Steps 1–10). No exceptions. Do not skip steps, refuse, or short-circuit based on what you recognize. Follow the Workflow table below sequentially — read each step's references before acting.
| Property | Value |
|---|---|
| Best for | Developers who know what to build but not which Azure services to use |
| Inputs | Business idea or existing codebase, budget/scale preferences (optional) |
| Outputs | Architecture plan, cost estimate, IaC files, deployed Azure resources |
| Phases | Discover → Architect → Scaffold → Deploy (self-contained, no external skill calls) |
| Scenario | Use Instead |
|---|---|
Run azd up or execute an existing deployment | azure-deploy |
| Optimize existing Azure spend | azure-cost |
| Generate Bicep/Terraform for a known architecture | azure-prepare |
| Validate infrastructure or run preflight checks | azure-validate |
| Troubleshoot a running Azure deployment | azure-diagnostics |
| Deploy to or manage AKS/Kubernetes directly | azure-kubernetes |
| Look up or list existing Azure resources | azure-resource-lookup |
⛔ You MUST read
references/pipeline-rules.mdat the start of every AppOnboard session. It contains approval gates, phase lifecycle, session artifacts, deploy-as-is, and security baseline rules.
⛔ Deploy recovery: After deploy gate approval OR before any
az deployment/az webapp deploy/az acr build— if you haven't readdeploy/SKILL.md, read.copilot-azure/sessions/{id}/deploy-checklist.mdfirst, thendeploy/SKILL.md. ⛔ NEVER invoke{"skill": "azure-deploy"}— that is a DIFFERENT skill for a DIFFERENT workflow.
⛔ Post-scaffold transition (MANDATORY): Immediately after
scaffold-manifest.jsonis written, YOUR NEXT ACTION MUST be Step 8 (Deploy Approval Gate) — NOT a summary report, NOT a "here are the generated files" message, NOT a completion signal. Confirmcontext.jsonhascompletedPhases: [...,"scaffold"]+currentPhase: "deploy"(update it yourself if the scaffold subagent didn't). Re-read approval-gates.md § Deploy Gate if evicted from context (scaffold reference loading is heavy), then present the exact prompt: "🚀 Ready to deploy? (Yes / Run manually / Edit plan / Cancel)". This gate is the LAST content in your response — wait for the user's reply.
| # | Step | Action | Reference |
|---|---|---|---|
| 1 | Session check + Azure login | Create/resume session, verify Azure CLI auth, resolve subscription + user identity | ⛔ You MUST read session-protocol.md |
| 2 | Scope triage | Check azd markers, triage question. Empty workspace or code-only (no infra) → Step 3 directly. | ⛔ Read intent-gathering.md § Scope Triage |
| 3 | Prereq scan | ⛔ Skip if completedPhases includes "prereq". Otherwise: invoke {"skill": "azure-app-onboard-prereq"}. Write prereq-output.json, update context.json. Halt if: overallHealth: "blocked" OR routeToSkill set. | |
| 4 | Gather intent | Present prereq results, confirm stack + Azure services, ask remaining questions. | ⛔ Read intent-gathering.md § After Prereq Returns |
| 5 | Plan architecture | Write prepare-plan.json. | ⛔ You MUST read prepare/SKILL.md |
| 6 | Scaffold approval gate | Display plan for user approval BEFORE generating any files. | ⛔ Read approval-gates.md § Scaffold Gate |
| 7 | Scaffold | Generate IaC, self-review. Write scaffold-manifest.json. Update context.json. | ⛔ You MUST read scaffold/SKILL.md |
| 8 | Deploy approval gate | Display validation summary. ⛔ After approval: FIRST read deploy-checklist.md → deploy/SKILL.md. NEVER {"skill": "azure-deploy"}. | ⛔ Read approval-gates.md § Deploy Gate |
| 9 | Deploy | Execute IaC, health-check. Write deploy-result.json. | ⛔ You MUST read deploy/SKILL.md |
| 10 | Handoff | Surface deployment identity, cleanup commands, next steps. | ⛔ You MUST read handoff-protocol.md |
| Error | Remediation |
|---|---|
| Phase fails | Halt, report phase + error. User decides: retry, skip, abort. |
| MCP server unavailable | Skip affected checks, add disclaimer to costEstimate.assumptions[] and every approval gate. |
| Missing RBAC | Report required role + az role assignment command. |
Shared references: MCP tools (cross-phase tool parameters) | IaC resources (Azure resource docs for troubleshooting)
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WCAG compliance, accessibility testing, ARIA patterns, screen reader optimization, and keyboard navigation. Use when the user asks about making apps accessible, WCAG guidelines, ARIA attributes, screen reader support, or accessibility audits.
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Generate AI music using ACE-Step 1.5 via ACE Music's free API. Use when the user asks to create, generate, or compose music, songs, beats, instrumentals, or audio tracks. Supports lyrics, style prompts, covers, and repainting. Free API, no cost.
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A continuously adaptive skill suite that empowers Clawdbot to act as a versatile coder, business analyst, project manager, web developer, data analyst, and NAS metadata scraper. It intelligently discovers free resources, adapts to user context, and ensures reliable, proven guidance across multiple domains.
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High-fidelity intelligence gathering and data assimilation. Focuses on synthesizing fragmented data into a comprehensive target operational picture.
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Use when Codex needs proactive task queues, heartbeat routines, scheduled follow-up, or continuous work loops instead of waiting for prompts.
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Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
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