azure-kusto-graph
Build and query Kusto graphs from natural language. Covers transient graphs (make-graph), persistent graph models/snapshots, pattern matching (graph-match),…
Generate deployment-ready infrastructure code from an architecture plan, verify it with adversarial self-review, and bridge to validation — all without deploying.
$ npx -y skills add microsoft/GitHub-Copilot-for-Azure --skill scaffold --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/scaffoldContext preview
The summary Claude sees to decide when to auto-load this skill.
Generate deployment-ready infrastructure code from an architecture plan, verify it with adversarial self-review, and bridge to validation — all without deploying.
Generate deployment-ready infrastructure code from an architecture plan, verify it with adversarial self-review, and bridge to validation — all without deploying.
| Property | Value | |----------|-------| | Parent | [azure-app-onboard](../SKILL.md) | | Best for | Turning `prepare-plan.json` service list into Bicep templates with secure-by-default patterns | | Inputs | `prepare-plan.json` (services, naming, quotas), `context.json` (overrides, components, repo info) | | Outputs | `scaffold-manifest.json`, generated IaC files in `infra/` | | Pipeline position | Phase 3 of 4: prereq → prepare → **scaffold** → deploy | | IaC format | Bicep (v1 default). Terraform when existing `.tf` detected or user override. |
Invoked by the `azure-app-onboard` orchestrator at Phase 3 when `prepare-plan.json` exists with `services[]`. Not directly user-routable in v1.
> **Return to orchestrator:** When complete, return control to `azure-app-onboard`. Do NOT directly invoke deploy — the orchestrator manages phase transitions.
| Scenario | Use Instead | |----------|-------------| | User-triggered IaC (no `prepare-plan.json`) | `azure-prepare` | | Subscription-scope landing zones | `azure-enterprise-infra-planner` | | Execute deployment (`azd up`) | `azure-deploy` (do NOT invoke from AppOnboard pipeline) |
> See [shared tools](../references/mcp-tool-reference.md) for cross-phase tools and global parameters. See [scaffold tools](references/mcp-tools.md) for full parameter tables.
| Tool | Sub-command | Purpose | Parameters | |------|-----------|---------|------------| | `mcp_azure_mcp_bicepschema` | `bicepschema_get` | ARM resource type schemas | `resource_type` (Required), `api_version` (Optional) | | `mcp_bicep_list_avm_metadata` | *(flat)* | AVM module catalog | None | | `mcp_bicep_get_bicep_best_practices` | *(flat)* | Bicep best practices | None | | `mcp_bicep_get_az_resource_type_schema` | *(flat)* | ARM resource type JSON schema | `azResourceType`, `apiVersion` (Required) | | `mcp_bicep_build_bicep` | *(flat)* | Validate `.bicep` files (self-review L3) | `filePath` (Required) | | `mcp_bicep_format_bicep_file` | *(flat)* | Format `.bicep` files (LF enforcement) | `filePath` (Required) | | `mcp_azure_mcp_deploy` | `deploy_iac_rules_get` | IaC best practices and rules | `deployment-tool`, `iac-type`, `resource-types` | | `mcp_azure_mcp_deploy` | `deploy_pipeline_guidance_get` | CI/CD pipeline config | `is-azd-project`, `pipeline-platform`, `deploy-option` | | `mcp_azure_mcp_get_azure_bestpractices` | `get_azure_bestpractices_get` | SDK/Functions best practices | `resource`, `action` | | `mcp_azure_mcp_azureterraformbestpractices` | *(flat)* | Terraform patterns (TF path only) | `resource_type` (Required) |
**Session folder:** `.copilot-azure/sessions/{uuid}/` — reads `prepare-plan.json` + `context.json`, writes `scaffold-manifest.json`.
1. **Read `prepare-plan.json`** — verify `services[]` exists, read `naming` config (especially `naming.resourcePrefix`, `naming.suffix`, `naming.resources[]`). Read resource group name from `context.json.azure.resourceGroup`. ⛔ **Use EXACTLY these names in generated IaC — do NOT invent names, derive them from `environmentName`, or append your own suffixes.** ⛔ **Use EXACTLY the names from `prepare-plan.json.naming.resources[]` as Bicep parameters. Do NOT derive names with `take()`, `substring()`, or string manipulation. The plan is the source of truth.** Missing → trigger prepare backfill via `azure-app-onboard` orchestrator. 2. **Read `context.json`** — check `overrides[]` for `iacFormat` preference, `detectedInfra[]` for existing `.tf`, `detectedInfraProvider` for cloud provider classification. 3. **Check workspace for existing IaC** — ⛔ **Skip** if `context.json.overrides[]` contains `ignoreExistingInfra: true`. Otherwise:
4. **Determine compute targets** — Check which compute targets are in the plan (App Service/Functions, Container Apps, or both) and whether PostgreSQL/Redis is present. Do NOT read any reference files — pass this info to the sub-agent at Step 5. 4b. **Pre-check API versions (main thread)** — MCP tool access is unreliable in `task` agents — call these in the main thread before dispatching. Call `mcp_bicep_list_az_resource_types_for_provider` (or `bicep-list_az_resource_types_for_provider`) once per provider namespace in `prepare-plan.json.services[]` (e.g., `Microsoft.Web`, `Microsoft.App`, `Microsoft.DBforPostgreSQL`, `Microsoft.Cache`, `Microsoft.KeyVault`, `Microsoft.ContainerRegistry`). Extract the latest GA API version (no `-preview`) for each resource type. Build an `apiVersions` map and pass it to the IaC gen sub-agent at Step 5. Fallback: if MCP unavailable, run `az provider show --namespace {ns} --query "resourceTypes[?resourceType=='{type}'].apiVersions[?!contains(@, 'preview')] | [0][0]" -o tsv` per resource type — this filters to GA-only and picks the latest. Pass `"MCP unavailable"` only if both MCP AND CLI fail. Sub-agent still validates generated Bicep via `az bicep build`.
> ⛔ **File boundary:** NEVER modify files outside `infra/`, `.copilot-azure/`. Scaffold only writes files — no install/build commands.
> ⛔ **Sub-agent delegation is MANDATORY for Steps 5, 6–9, and 10–12.** Each step reads its `subagent-*.md` template, then dispatches a `task` call. Do NOT read any re
GitHub Copilot for Azure is a set of extensions for Visual Studio, VS Code, and Claude Code designed to streamline the process of developing for Azure.
Repo: microsoft/GitHub-Copilot-for-Azure
Build and query Kusto graphs from natural language. Covers transient graphs (make-graph), persistent graph models/snapshots, pattern matching (graph-match),…
Apply IRQL graph functions to KQL or IRQL query results for Kusto Explorer visualization. Generates Lift_To_Graph mappings and composes Graph_Render_View,…
Compose IRQL (Incident Response Query Language) queries for Kusto cybersecurity investigations. Translates natural language hunting questions into composable…
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first…
Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to…
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR.…