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* feat: add flowstudio-power-automate-debug and flowstudio-power-automate-build skills Two companion skills for the FlowStudio Power Automate MCP server: - flowstudio-power-automate-debug: Debug workflow for failed Power Automate cloud flow runs - flowstudio-power-automate-build: Build & deploy flows from natural language descriptions Both require a FlowStudio MCP subscription: https://flowstudio.app These complement the existing flowstudio-power-automate-mcp skill (merged in PR #896). * fix: address all review comments — README, cross-refs, response shapes, step numbering - Add skills to docs/README.skills.md (fixes validate-readme CI check) - Update cross-skill references to use flowstudio- prefix (#1, #4, #7, #9) - Fix get_live_flow_run_action_outputs: returns array, index [0] (#2, #3) - Renumber Step 6→5, Step 7→6 — remove gap in build workflow (#8) - Fix connectionName note: it's the key, not the GUID (#10) - Remove invalid arrow function from Filter array expression (#11) * feat: add flowstudio-power-automate plugin bundling all 3 skills Plugin bundles: - flowstudio-power-automate-mcp (core connection & CRUD) - flowstudio-power-automate-debug (debug failed runs) - flowstudio-power-automate-build (build & deploy flows) Install: copilot plugin install flowstudio-power-automate@awesome-copilot Per @aaronpowell's suggestion in review.
323 lines
11 KiB
Markdown
323 lines
11 KiB
Markdown
---
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name: flowstudio-power-automate-debug
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description: >-
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Debug failing Power Automate cloud flows using the FlowStudio MCP server.
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Load this skill when asked to: debug a flow, investigate a failed run, why is
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this flow failing, inspect action outputs, find the root cause of a flow error,
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fix a broken Power Automate flow, diagnose a timeout, trace a DynamicOperationRequestFailure,
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check connector auth errors, read error details from a run, or troubleshoot
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expression failures. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app
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---
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# Power Automate Debugging with FlowStudio MCP
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A step-by-step diagnostic process for investigating failing Power Automate
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cloud flows through the FlowStudio MCP server.
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**Prerequisite**: A FlowStudio MCP server must be reachable with a valid JWT.
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See the `flowstudio-power-automate-mcp` skill for connection setup.
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Subscribe at https://mcp.flowstudio.app
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---
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## Source of Truth
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> **Always call `tools/list` first** to confirm available tool names and their
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> parameter schemas. Tool names and parameters may change between server versions.
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> This skill covers response shapes, behavioral notes, and diagnostic patterns —
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> things `tools/list` cannot tell you. If this document disagrees with `tools/list`
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> or a real API response, the API wins.
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---
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## Python Helper
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```python
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import json, urllib.request
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MCP_URL = "https://mcp.flowstudio.app/mcp"
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MCP_TOKEN = "<YOUR_JWT_TOKEN>"
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def mcp(tool, **kwargs):
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payload = json.dumps({"jsonrpc": "2.0", "id": 1, "method": "tools/call",
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"params": {"name": tool, "arguments": kwargs}}).encode()
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req = urllib.request.Request(MCP_URL, data=payload,
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headers={"x-api-key": MCP_TOKEN, "Content-Type": "application/json",
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"User-Agent": "FlowStudio-MCP/1.0"})
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try:
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resp = urllib.request.urlopen(req, timeout=120)
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except urllib.error.HTTPError as e:
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body = e.read().decode("utf-8", errors="replace")
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raise RuntimeError(f"MCP HTTP {e.code}: {body[:200]}") from e
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raw = json.loads(resp.read())
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if "error" in raw:
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raise RuntimeError(f"MCP error: {json.dumps(raw['error'])}")
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return json.loads(raw["result"]["content"][0]["text"])
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ENV = "<environment-id>" # e.g. Default-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
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```
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---
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## FlowStudio for Teams: Fast-Path Diagnosis (Skip Steps 2–4)
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If you have a FlowStudio for Teams subscription, `get_store_flow_errors`
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returns per-run failure data including action names and remediation hints
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in a single call — no need to walk through live API steps.
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```python
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# Quick failure summary
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summary = mcp("get_store_flow_summary", environmentName=ENV, flowName=FLOW_ID)
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# {"totalRuns": 100, "failRuns": 10, "failRate": 0.1,
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# "averageDurationSeconds": 29.4, "maxDurationSeconds": 158.9,
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# "firstFailRunRemediation": "<hint or null>"}
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print(f"Fail rate: {summary['failRate']:.0%} over {summary['totalRuns']} runs")
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# Per-run error details (requires active monitoring to be configured)
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errors = mcp("get_store_flow_errors", environmentName=ENV, flowName=FLOW_ID)
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if errors:
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for r in errors[:3]:
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print(r["startTime"], "|", r.get("failedActions"), "|", r.get("remediationHint"))
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# If errors confirms the failing action → jump to Step 6 (apply fix)
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else:
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# Store doesn't have run-level detail for this flow — use live tools (Steps 2–5)
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pass
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```
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For the full governance record (description, complexity, tier, connector list):
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```python
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record = mcp("get_store_flow", environmentName=ENV, flowName=FLOW_ID)
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# {"displayName": "My Flow", "state": "Started",
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# "runPeriodTotal": 100, "runPeriodFailRate": 0.1, "runPeriodFails": 10,
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# "runPeriodDurationAverage": 29410.8, ← milliseconds
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# "runError": "{\"code\": \"EACCES\", ...}", ← JSON string, parse it
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# "description": "...", "tier": "Premium", "complexity": "{...}"}
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if record.get("runError"):
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last_err = json.loads(record["runError"])
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print("Last run error:", last_err)
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```
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---
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## Step 1 — Locate the Flow
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```python
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result = mcp("list_live_flows", environmentName=ENV)
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# Returns a wrapper object: {mode, flows, totalCount, error}
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target = next(f for f in result["flows"] if "My Flow Name" in f["displayName"])
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FLOW_ID = target["id"] # plain UUID — use directly as flowName
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print(FLOW_ID)
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```
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---
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## Step 2 — Find the Failing Run
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```python
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runs = mcp("get_live_flow_runs", environmentName=ENV, flowName=FLOW_ID, top=5)
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# Returns direct array (newest first):
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# [{"name": "08584296068667933411438594643CU15",
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# "status": "Failed",
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# "startTime": "2026-02-25T06:13:38.6910688Z",
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# "endTime": "2026-02-25T06:15:24.1995008Z",
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# "triggerName": "manual",
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# "error": {"code": "ActionFailed", "message": "An action failed..."}},
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# {"name": "...", "status": "Succeeded", "error": null, ...}]
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for r in runs:
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print(r["name"], r["status"], r["startTime"])
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RUN_ID = next(r["name"] for r in runs if r["status"] == "Failed")
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```
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---
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## Step 3 — Get the Top-Level Error
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```python
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err = mcp("get_live_flow_run_error",
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environmentName=ENV, flowName=FLOW_ID, runName=RUN_ID)
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# Returns:
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# {
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# "runName": "08584296068667933411438594643CU15",
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# "failedActions": [
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# {"actionName": "Apply_to_each_prepare_workers", "status": "Failed",
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# "error": {"code": "ActionFailed", "message": "An action failed..."},
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# "startTime": "...", "endTime": "..."},
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# {"actionName": "HTTP_find_AD_User_by_Name", "status": "Failed",
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# "code": "NotSpecified", "startTime": "...", "endTime": "..."}
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# ],
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# "allActions": [
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# {"actionName": "Apply_to_each", "status": "Skipped"},
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# {"actionName": "Compose_WeekEnd", "status": "Succeeded"},
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# ...
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# ]
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# }
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# failedActions is ordered outer-to-inner. The ROOT cause is the LAST entry:
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root = err["failedActions"][-1]
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print(f"Root action: {root['actionName']} → code: {root.get('code')}")
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# allActions shows every action's status — useful for spotting what was Skipped
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# See common-errors.md to decode the error code.
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```
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---
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## Step 4 — Read the Flow Definition
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```python
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defn = mcp("get_live_flow", environmentName=ENV, flowName=FLOW_ID)
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actions = defn["properties"]["definition"]["actions"]
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print(list(actions.keys()))
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```
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Find the failing action in the definition. Inspect its `inputs` expression
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to understand what data it expects.
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---
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## Step 5 — Inspect Action Outputs (Walk Back from Failure)
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For each action **leading up to** the failure, inspect its runtime output:
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```python
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for action_name in ["Compose_WeekEnd", "HTTP_Get_Data", "Parse_JSON"]:
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result = mcp("get_live_flow_run_action_outputs",
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environmentName=ENV,
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flowName=FLOW_ID,
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runName=RUN_ID,
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actionName=action_name)
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# Returns an array — single-element when actionName is provided
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out = result[0] if result else {}
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print(action_name, out.get("status"))
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print(json.dumps(out.get("outputs", {}), indent=2)[:500])
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```
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> ⚠️ Output payloads from array-processing actions can be very large.
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> Always slice (e.g. `[:500]`) before printing.
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---
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## Step 6 — Pinpoint the Root Cause
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### Expression Errors (e.g. `split` on null)
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If the error mentions `InvalidTemplate` or a function name:
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1. Find the action in the definition
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2. Check what upstream action/expression it reads
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3. Inspect that upstream action's output for null / missing fields
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```python
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# Example: action uses split(item()?['Name'], ' ')
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# → null Name in the source data
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result = mcp("get_live_flow_run_action_outputs", ..., actionName="Compose_Names")
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# Returns a single-element array; index [0] to get the action object
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if not result:
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print("No outputs returned for Compose_Names")
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names = []
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else:
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names = result[0].get("outputs", {}).get("body") or []
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nulls = [x for x in names if x.get("Name") is None]
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print(f"{len(nulls)} records with null Name")
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```
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### Wrong Field Path
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Expression `triggerBody()?['fieldName']` returns null → `fieldName` is wrong.
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Check the trigger output shape with:
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```python
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mcp("get_live_flow_run_action_outputs", ..., actionName="<trigger-action-name>")
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```
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### Connection / Auth Failures
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Look for `ConnectionAuthorizationFailed` — the connection owner must match the
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service account running the flow. Cannot fix via API; fix in PA designer.
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---
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## Step 7 — Apply the Fix
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**For expression/data issues**:
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```python
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defn = mcp("get_live_flow", environmentName=ENV, flowName=FLOW_ID)
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acts = defn["properties"]["definition"]["actions"]
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# Example: fix split on potentially-null Name
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acts["Compose_Names"]["inputs"] = \
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"@coalesce(item()?['Name'], 'Unknown')"
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conn_refs = defn["properties"]["connectionReferences"]
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result = mcp("update_live_flow",
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environmentName=ENV,
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flowName=FLOW_ID,
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definition=defn["properties"]["definition"],
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connectionReferences=conn_refs)
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print(result.get("error")) # None = success
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```
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> ⚠️ `update_live_flow` always returns an `error` key.
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> A value of `null` (Python `None`) means success.
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---
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## Step 8 — Verify the Fix
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```python
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# Resubmit the failed run
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resubmit = mcp("resubmit_live_flow_run",
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environmentName=ENV, flowName=FLOW_ID, runName=RUN_ID)
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print(resubmit)
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# Wait ~30 s then check
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import time; time.sleep(30)
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new_runs = mcp("get_live_flow_runs", environmentName=ENV, flowName=FLOW_ID, top=3)
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print(new_runs[0]["status"]) # Succeeded = done
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```
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### Testing HTTP-Triggered Flows
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For flows with a `Request` (HTTP) trigger, use `trigger_live_flow` instead
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of `resubmit_live_flow_run` to test with custom payloads:
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```python
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# First inspect what the trigger expects
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schema = mcp("get_live_flow_http_schema",
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environmentName=ENV, flowName=FLOW_ID)
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print("Expected body schema:", schema.get("triggerSchema"))
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print("Response schemas:", schema.get("responseSchemas"))
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# Trigger with a test payload
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result = mcp("trigger_live_flow",
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environmentName=ENV,
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flowName=FLOW_ID,
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body={"name": "Test User", "value": 42})
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print(f"Status: {result['status']}, Body: {result.get('body')}")
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```
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> `trigger_live_flow` handles AAD-authenticated triggers automatically.
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> Only works for flows with a `Request` (HTTP) trigger type.
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---
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## Quick-Reference Diagnostic Decision Tree
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| Symptom | First Tool to Call | What to Look For |
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|---|---|---|
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| Flow shows as Failed | `get_live_flow_run_error` | `failedActions[-1]["actionName"]` = root cause |
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| Expression crash | `get_live_flow_run_action_outputs` on prior action | null / wrong-type fields in output body |
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| Flow never starts | `get_live_flow` | check `properties.state` = "Started" |
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| Action returns wrong data | `get_live_flow_run_action_outputs` | actual output body vs expected |
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| Fix applied but still fails | `get_live_flow_runs` after resubmit | new run `status` field |
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---
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## Reference Files
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- [common-errors.md](references/common-errors.md) — Error codes, likely causes, and fixes
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- [debug-workflow.md](references/debug-workflow.md) — Full decision tree for complex failures
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## Related Skills
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- `flowstudio-power-automate-mcp` — Core connection setup and operation reference
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- `flowstudio-power-automate-build` — Build and deploy new flows
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