| name | chaos-impact |
| description | Synthesize an Azure Monitor impact report for a Chaos Studio v2 ScenarioRun: pulls the run, walks targeted resources, queries metrics/logs/activity-log/alerts over the run window ± buffer, and renders a Markdown + JSON impact card. |
ChaosImpact — Post-Run Azure Monitor Synthesis
⛔ ABSOLUTE RULE: Do NOT improvise, skip, or substitute any step. On ANY error, STOP and wait for the user.
When to use this skill (vs. the MCP server)
This skill is the human-interactive path: it resolves run context from the
shared startchaos-state.json, prompts for missing inputs via exit codes, and
renders a Markdown card plus a JSON sidecar. Use it when there is a user in the
loop — typically right after /start-chaos (or as a post-step of it).
If you are an autonomous agent with no user to prompt, call the three
Monitor tools on the chaos-studio MCP server directly (monitor_query_metrics,
monitor_query_logs, monitor_search_activity_log) and assemble your own
report. The PowerShell skill and the MCP tools are two independent surfaces
over the same Azure endpoints — neither calls the other.
Both surfaces target Microsoft.Chaos 2026-05-01-preview plus the pinned
Azure Monitor API versions in scripts/Constants.ps1, and use the local
az login session for auth.
How It Works
All synthesis logic lives in scripts/Invoke-ChaosImpact.ps1. The script
resolves the ScenarioRun, discovers Log Analytics workspaces via diagnostic
settings, runs the Monitor query fan-out, classifies signals, and writes both
artifacts.
The AI orchestrator's only job is:
- Set
$env:STARTCHAOS_STATE_PATH to ${SESSION_DIR}/startchaos-state.json
(the skill reads but does not write this file).
- Run the script with
-ScenarioRunId <id> (positional accepted).
- Handle exit codes that require user input (see below).
- Re-run the script with the user's answers as parameters.
Running the Script
$env:STARTCHAOS_STATE_PATH = "<session-dir>/startchaos-state.json"
& "<skill-dir>/scripts/Invoke-ChaosImpact.ps1" -ScenarioRunId <runId> @extraArgs
When invoked standalone (no prior start-chaos state file), the orchestrator
must supply -SubscriptionId, -ResourceGroup, -WorkspaceName, and
-ScenarioName — otherwise the script exits 2.
Exit Codes → AI Actions
| Exit | Meaning | AI Action |
|---|
| 0 | Report generated | Done — print the Markdown card from script output. |
| 1 | Hard error | STOP. Render the error from script output. Wait for user. |
| 2 | Missing run context | ask_user for any of: -SubscriptionId, -ResourceGroup, -WorkspaceName, -ScenarioName, -ScenarioRunId. Re-run with the supplied parameters. |
| 3 | Log Analytics workspace not discoverable for ≥ 1 resource, AND -LogAnalyticsWorkspaceId not supplied | ask_user whether to (a) supply a workspace ID (re-run with -LogAnalyticsWorkspaceId <id>) or (b) proceed without log signals (re-run with -LogAnalyticsWorkspaceId none). |
| 4 | Permission gap (caller lacks Monitoring Reader on one or more target resource groups) (Epic 3 — not yet implemented) | ask_user to confirm best-effort partial report (re-run with -AllowPartial) or abort. |
Script Parameters
| Parameter | Description |
|---|
-ScenarioRunId | Required (positional). The ScenarioRun resource name. |
-SubscriptionId / -ResourceGroup / -WorkspaceName / -ScenarioName | Run context. Read from startchaos-state.json when omitted; required otherwise. |
-Buffer | ISO-8601 duration added before/after the run window. Default PT5M. |
-LogAnalyticsWorkspaceId | Optional override when diag-settings discovery fails for some resources. Pass none to explicitly skip log signals. |
-MaxResources | Per-run resource cap. Default 50. Instance-level targets (VMSS / AKS) are collapsed to parent before counting. |
-OutputDir | Where to drop artifacts. Default $env:STARTCHAOS_SESSION_DIR or current directory. |
-IncludeBaseline | When set, also computes baseline samples (the -Buffer × 2 window before run start). Default on. |
-Format | markdown, json, or both. Default both. |
-AllowPartial | Continue past permission gaps and emit a partial report. (Epic 3 — not yet implemented; currently accepted but has no effect.) |
What the Script Handles (no AI logic needed)
- Run resolution and targeted-resource flattening (collapses instance-level → parent)
MaxResources cap with explicit coverage caveats- Diagnostic-settings discovery + per-resource workspace caching
- Azure Monitor metrics / Log Analytics / Activity Log / Alerts / Service Health fan-out
- Baseline subtraction and signal classification
- Markdown report card + JSON sidecar artifact
- All error cards with remediation commands
