Agent skill

Power Automate Build

by LeoYeAI in LeoYeAI/openclaw-master-skills

Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server.

MITAuto-check passedAgent Workflows

Install Power Automate Build

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill power-automate-build -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills power-automate-build --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/power-automate-build .claude/skills/power-automate-build && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
power-automate-build
GitHub stars
2.2k
Token cost
~4.3k tokens
SKILL.md length
1,024 words
Files
8 (incl. references)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server.

  • Works in 6 steps: Safety Check: Does the Flow Already Exist? → Obtain Connection References → Build the Flow Definition → …
  • Tasks that involve MCP servers
  • SKILL.md covers Source of Truth, Python Helper, Step 1 — Safety Check: Does… and Step 2 — Obtain Connection…, plus 7 more sections
  • Reaches mcp.flowstudio.app and make.powerautomate.com; needs MCP_TOKEN

What it does

Power Automate Build is an agent skill from LeoYeAI/openclaw-master-skills. Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. Load this skill when asked to: create a flow, build a new flow, deploy a flow definition, scaffold a Power Automate workflow, construct a flow JSON, update an existing flow's actions, patch a flow definition, add actions to a flow, wire up connections, or generate a workflow definition from scratch. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app

Its SKILL.md is about 4.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `_meta.json`, `references/action-patterns-connectors.md` and `references/action-patterns-core.md`).

It sits in Agent Workflows, covering MCP servers. It works with Power Automate and Model Context Protocol. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Tasks that involve MCP servers

Example prompts

  • “/power-automate-build”

Requirements

  • Python 3
  • A credential in FLOWSTUDIO_MCP_TOKEN
  • A credential in MCP_TOKEN

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Safety Check: Does the Flow Already Exist?
  2. Obtain Connection References
  3. Build the Flow Definition
  4. Deploy (Create or Update)
  5. Verify the Deployment
  6. Test the Flow

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • mcp.flowstudio.app
    • make.powerautomate.com
    • schema.management.azure.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • MCP_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Power Automate Build loads about 4.3k tokens when it runs, and up to ~21k if it reads all its reference files. Until then it costs about 120 tokens; SKILL.md has 1,024 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~120
When it runs · the whole SKILL.md, loaded when a task matches
~4.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~21k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,024 words, ~4,326 tokens.

Download SKILL.mdSave it as .claude/skills/power-automate-build/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
power-automate-build
description
Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. Load this skill when asked to: create a flow, build a new flow, deploy a flow definition, scaffold a Power Automate workflow, construct a flow JSON, update an existing flow's actions, patch a flow definition, add actions to a flow, wire up connections, or generate a workflow definition from scratch. Requires a FlowStudio MCP subscription — see https://mcp.flowstudio.app

Build & Deploy Power Automate Flows with FlowStudio MCP

Step-by-step guide for constructing and deploying Power Automate cloud flows programmatically through the FlowStudio MCP server.

Prerequisite: A FlowStudio MCP server must be reachable with a valid JWT. See the power-automate-mcp skill for connection setup.
Subscribe at https://mcp.flowstudio.app


Source of Truth

Always call tools/list first to confirm available tool names and their parameter schemas. Tool names and parameters may change between server versions. This skill covers response shapes, behavioral notes, and build patterns — things tools/list cannot tell you. If this document disagrees with tools/list or a real API response, the API wins.


Python Helper

python
import json, urllib.request

MCP_URL   = "https://mcp.flowstudio.app/mcp"
MCP_TOKEN = "<YOUR_JWT_TOKEN>"

def mcp(tool, **kwargs):
    payload = json.dumps({"jsonrpc": "2.0", "id": 1, "method": "tools/call",
                          "params": {"name": tool, "arguments": kwargs}}).encode()
    req = urllib.request.Request(MCP_URL, data=payload,
        headers={"x-api-key": MCP_TOKEN, "Content-Type": "application/json",
                 "User-Agent": "FlowStudio-MCP/1.0"})
    try:
        resp = urllib.request.urlopen(req, timeout=120)
    except urllib.error.HTTPError as e:
        body = e.read().decode("utf-8", errors="replace")
        raise RuntimeError(f"MCP HTTP {e.code}: {body[:200]}") from e
    raw = json.loads(resp.read())
    if "error" in raw:
        raise RuntimeError(f"MCP error: {json.dumps(raw['error'])}")
    return json.loads(raw["result"]["content"][0]["text"])

ENV = "<environment-id>"  # e.g. Default-xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx

Step 1 — Safety Check: Does the Flow Already Exist?

Always look before you build to avoid duplicates:

python
results = mcp("list_store_flows",
    environmentName=ENV, searchTerm="My New Flow")

# list_store_flows returns a direct array (no wrapper object)
if len(results) > 0:
    # Flow exists — modify rather than create
    # id format is "envId.flowId" — split to get the flow UUID
    FLOW_ID = results[0]["id"].split(".", 1)[1]
    print(f"Existing flow: {FLOW_ID}")
    defn = mcp("get_live_flow", environmentName=ENV, flowName=FLOW_ID)
else:
    print("Flow not found — building from scratch")
    FLOW_ID = None

Step 2 — Obtain Connection References

Every connector action needs a connectionName that points to a key in the flow's connectionReferences map. That key links to an authenticated connection in the environment.

MANDATORY: You MUST call list_live_connections first — do NOT ask the user for connection names or GUIDs. The API returns the exact values you need. Only prompt the user if the API confirms that required connections are missing.

2a — Always call list_live_connections first
python
conns = mcp("list_live_connections", environmentName=ENV)

# Filter to connected (authenticated) connections only
active = [c for c in conns["connections"]
          if c["statuses"][0]["status"] == "Connected"]

# Build a lookup: connectorName → connectionName (id)
conn_map = {}
for c in active:
    conn_map[c["connectorName"]] = c["id"]

print(f"Found {len(active)} active connections")
print("Available connectors:", list(conn_map.keys()))
2b — Determine which connectors the flow needs

Based on the flow you are building, identify which connectors are required. Common connector API names:

ConnectorAPI name
SharePointshared_sharepointonline
Outlook / Office 365shared_office365
Teamsshared_teams
Approvalsshared_approvals
OneDrive for Businessshared_onedriveforbusiness
Excel Online (Business)shared_excelonlinebusiness
Dataverseshared_commondataserviceforapps
Microsoft Formsshared_microsoftforms

Flows that need NO connections (e.g. Recurrence + Compose + HTTP only) can skip the rest of Step 2 — omit connectionReferences from the deploy call.

2c — If connections are missing, guide the user
python
connectors_needed = ["shared_sharepointonline", "shared_office365"]  # adjust per flow

missing = [c for c in connectors_needed if c not in conn_map]

if not missing:
    print("✅ All required connections are available — proceeding to build")
else:
    # ── STOP: connections must be created interactively ──
    # Connections require OAuth consent in a browser — no API can create them.
    print("⚠️  The following connectors have no active connection in this environment:")
    for c in missing:
        friendly = c.replace("shared_", "").replace("onlinebusiness", " Online (Business)")
        print(f"   • {friendly}  (API name: {c})")
    print()
    print("Please create the missing connections:")
    print("  1. Open https://make.powerautomate.com/connections")
    print("  2. Select the correct environment from the top-right picker")
    print("  3. Click '+ New connection' for each missing connector listed above")
    print("  4. Sign in and authorize when prompted")
    print("  5. Tell me when done — I will re-check and continue building")
    # DO NOT proceed to Step 3 until the user confirms.
    # After user confirms, re-run Step 2a to refresh conn_map.
2d — Build the connectionReferences block

Only execute this after 2c confirms no missing connectors:

python
connection_references = {}
for connector in connectors_needed:
    connection_references[connector] = {
        "connectionName": conn_map[connector],   # the GUID from list_live_connections
        "source": "Invoker",
        "id": f"/providers/Microsoft.PowerApps/apis/{connector}"
    }

IMPORTANT — host.connectionName in actions: When building actions in Step 3, set host.connectionName to the key from this map (e.g. shared_teams), NOT the connection GUID. The GUID only goes inside the connectionReferences entry. The engine matches the action's host.connectionName to the key to find the right connection.

Alternative — if you already have a flow using the same connectors, you can extract connectionReferences from its definition:

python
ref_flow = mcp("get_live_flow", environmentName=ENV, flowName="<existing-flow-id>")
connection_references = ref_flow["properties"]["connectionReferences"]

See the power-automate-mcp skill's connection-references.md reference for the full connection reference structure.


Step 3 — Build the Flow Definition

Construct the definition object. See flow-schema.md for the full schema and these action pattern references for copy-paste templates:

python
definition = {
    "$schema": "https://schema.management.azure.com/providers/Microsoft.Logic/schemas/2016-06-01/workflowdefinition.json#",
    "contentVersion": "1.0.0.0",
    "triggers": { ... },   # see trigger-types.md / build-patterns.md
    "actions": { ... }     # see ACTION-PATTERNS-*.md / build-patterns.md
}

See build-patterns.md for complete, ready-to-use flow definitions covering Recurrence+SharePoint+Teams, HTTP triggers, and more.


Step 4 — Deploy (Create or Update)

update_live_flow handles both creation and updates in a single tool.

Create a new flow (no existing flow)

Omit flowName — the server generates a new GUID and creates via PUT:

python
result = mcp("update_live_flow",
    environmentName=ENV,
    # flowName omitted → creates a new flow
    definition=definition,
    connectionReferences=connection_references,
    displayName="Overdue Invoice Notifications",
    description="Weekly SharePoint → Teams notification flow, built by agent"
)

if result.get("error") is not None:
    print("Create failed:", result["error"])
else:
    # Capture the new flow ID for subsequent steps
    FLOW_ID = result["created"]
    print(f"✅ Flow created: {FLOW_ID}")
Update an existing flow

Provide flowName to PATCH:

python
result = mcp("update_live_flow",
    environmentName=ENV,
    flowName=FLOW_ID,
    definition=definition,
    connectionReferences=connection_references,
    displayName="My Updated Flow",
    description="Updated by agent on " + __import__('datetime').datetime.utcnow().isoformat()
)

if result.get("error") is not None:
    print("Update failed:", result["error"])
else:
    print("Update succeeded:", result)

⚠️ update_live_flow always returns an error key. null (Python None) means success — do not treat the presence of the key as failure.

⚠️ description is required for both create and update.

Common deployment errors
Error message (contains)CauseFix
missing from connectionReferencesAn action's host.connectionName references a key that doesn't exist in the connectionReferences mapEnsure host.connectionName uses the key from connectionReferences (e.g. shared_teams), not the raw GUID
ConnectionAuthorizationFailed / 403The connection GUID belongs to another user or is not authorizedRe-run Step 2a and use a connection owned by the current x-api-key user
InvalidTemplate / InvalidDefinitionSyntax error in the definition JSONCheck runAfter chains, expression syntax, and action type spelling
ConnectionNotConfiguredA connector action exists but the connection GUID is invalid or expiredRe-check list_live_connections for a fresh GUID

Step 5 — Verify the Deployment

python
check = mcp("get_live_flow", environmentName=ENV, flowName=FLOW_ID)

# Confirm state
print("State:", check["properties"]["state"])  # Should be "Started"

# Confirm the action we added is there
acts = check["properties"]["definition"]["actions"]
print("Actions:", list(acts.keys()))

Show full SKILL.md (427 more words)Show less

Step 6 — Test the Flow

MANDATORY: Before triggering any test run, ask the user for confirmation. Running a flow has real side effects — it may send emails, post Teams messages, write to SharePoint, start approvals, or call external APIs. Explain what the flow will do and wait for explicit approval before calling trigger_live_flow or resubmit_live_flow_run.

Updated flows (have prior runs)

The fastest path — resubmit the most recent run:

python
runs = mcp("get_live_flow_runs", environmentName=ENV, flowName=FLOW_ID, top=1)
if runs:
    result = mcp("resubmit_live_flow_run",
        environmentName=ENV, flowName=FLOW_ID, runName=runs[0]["name"])
    print(result)
Flows already using an HTTP trigger

Fire directly with a test payload:

python
schema = mcp("get_live_flow_http_schema",
    environmentName=ENV, flowName=FLOW_ID)
print("Expected body:", schema.get("triggerSchema"))

result = mcp("trigger_live_flow",
    environmentName=ENV, flowName=FLOW_ID,
    body={"name": "Test", "value": 1})
print(f"Status: {result['status']}")
Brand-new non-HTTP flows (Recurrence, connector triggers, etc.)

A brand-new Recurrence or connector-triggered flow has no runs to resubmit and no HTTP endpoint to call. Deploy with a temporary HTTP trigger first, test the actions, then swap to the production trigger.

7a — Save the real trigger, deploy with a temporary HTTP trigger
python
# Save the production trigger you built in Step 3
production_trigger = definition["triggers"]

# Replace with a temporary HTTP trigger
definition["triggers"] = {
    "manual": {
        "type": "Request",
        "kind": "Http",
        "inputs": {
            "schema": {}
        }
    }
}

# Deploy (create or update) with the temp trigger
result = mcp("update_live_flow",
    environmentName=ENV,
    flowName=FLOW_ID,       # omit if creating new
    definition=definition,
    connectionReferences=connection_references,
    displayName="Overdue Invoice Notifications",
    description="Deployed with temp HTTP trigger for testing")

if result.get("error") is not None:
    print("Deploy failed:", result["error"])
else:
    if not FLOW_ID:
        FLOW_ID = result["created"]
    print(f"✅ Deployed with temp HTTP trigger: {FLOW_ID}")
7b — Fire the flow and check the result
python
# Trigger the flow
test = mcp("trigger_live_flow",
    environmentName=ENV, flowName=FLOW_ID)
print(f"Trigger response status: {test['status']}")

# Wait for the run to complete
import time; time.sleep(15)

# Check the run result
runs = mcp("get_live_flow_runs",
    environmentName=ENV, flowName=FLOW_ID, top=1)
run = runs[0]
print(f"Run {run['name']}: {run['status']}")

if run["status"] == "Failed":
    err = mcp("get_live_flow_run_error",
        environmentName=ENV, flowName=FLOW_ID, runName=run["name"])
    root = err["failedActions"][-1]
    print(f"Root cause: {root['actionName']} → {root.get('code')}")
    # Debug and fix the definition before proceeding
    # See power-automate-debug skill for full diagnosis workflow
7c — Swap to the production trigger

Once the test run succeeds, replace the temporary HTTP trigger with the real one:

python
# Restore the production trigger
definition["triggers"] = production_trigger

result = mcp("update_live_flow",
    environmentName=ENV,
    flowName=FLOW_ID,
    definition=definition,
    connectionReferences=connection_references,
    description="Swapped to production trigger after successful test")

if result.get("error") is not None:
    print("Trigger swap failed:", result["error"])
else:
    print("✅ Production trigger deployed — flow is live")

Why this works: The trigger is just the entry point — the actions are identical regardless of how the flow starts. Testing via HTTP trigger exercises all the same Compose, SharePoint, Teams, etc. actions.

Connector triggers (e.g. "When an item is created in SharePoint"): If actions reference triggerBody() or triggerOutputs(), pass a representative test payload in trigger_live_flow's body parameter that matches the shape the connector trigger would produce.


Gotchas

MistakeConsequencePrevention
Missing connectionReferences in deploy400 "Supply connectionReferences"Always call list_live_connections first
"operationOptions" missing on ForeachParallel execution, race conditions on writesAlways add "Sequential"
union(old_data, new_data)Old values override new (first-wins)Use union(new_data, old_data)
split() on potentially-null stringInvalidTemplate crashWrap with coalesce(field, '')
Checking result["error"] existsAlways present; true error is != nullUse result.get("error") is not None
Flow deployed but state is "Stopped"Flow won't run on scheduleCheck connection auth; re-enable
Teams "Chat with Flow bot" recipient as object400 GraphUserDetailNotFoundUse plain string with trailing semicolon (see below)
Teams PostMessageToConversation — Recipient Formats

The body/recipient parameter format depends on the location value:

Locationbody/recipient formatExample
Chat with Flow botPlain email string with trailing semicolon"user@contoso.com;"
ChannelObject with groupId and channelId{"groupId": "...", "channelId": "..."}

Common mistake: passing {"to": "user@contoso.com"} for "Chat with Flow bot" returns a 400 GraphUserDetailNotFound error. The API expects a plain string.


Reference Files

  • power-automate-mcp — Core connection setup and tool reference
  • power-automate-debug — Debug failing flows after deployment

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (references) in skills/power-automate-build of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json
  • references/action-patterns-connectors.md
  • references/action-patterns-core.md
  • references/action-patterns-data.md
  • references/build-patterns.md
  • references/flow-schema.md
  • references/trigger-types.md

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Power Automate Build next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Power Automate Build compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Power Automate Build this skillLeoYeAI/openclaw-master-skills2.2k—~4.3kAutomated safety check: PassMIT
Dv Connectmicrosoft/Dataverse-skills243—~5kAutomated safety check: NotesMIT
Flowstudio Power Automate Buildgithub/awesome-copilot40k2 repos~5kAutomated safety check: PassMIT
Flowstudio Power Automate MCPgithub/awesome-copilot40k1 repos~3.4kAutomated safety check: PassMIT
MCP Copilot Studio Server Generatorgithub/awesome-copilot40k1 repos~1.1kAutomated safety check: PassMIT
Power Platform MCP Connector Suitegithub/awesome-copilot40k1 repos~1.6kAutomated safety check: PassMIT

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Categories

Questions about Power Automate Build

What does Power Automate Build do?

Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. Power Automate Build is an agent skill from LeoYeAI/openclaw-master-skills. Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server.

When should I use Power Automate Build?

Power Automate Build fits situations like: tasks that involve MCP servers.

How do I install Power Automate Build in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill power-automate-build -a claude-code`. Or copy the skill folder (skills/power-automate-build in LeoYeAI/openclaw-master-skills) into .claude/skills/power-automate-build in your project. Claude Code loads it when a task matches its description.

How do I install Power Automate Build in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill power-automate-build -a codex`. Or copy the skill folder (skills/power-automate-build in LeoYeAI/openclaw-master-skills) into .agents/skills/power-automate-build in your project. Codex loads it when a task matches its description.

Can I use Power Automate Build in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill power-automate-build -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/power-automate-build, .gemini/skills/power-automate-build, .github/skills/power-automate-build and .opencode/skills/power-automate-build in your project.

What does Power Automate Build need to run?

Going by SKILL.md and its folder, Power Automate Build needs credentials named MCP_TOKEN. Our summary lists: Python 3; A credential in FLOWSTUDIO_MCP_TOKEN; A credential in MCP_TOKEN.

Does Power Automate Build access the network?

SKILL.md names 3 domains. In commands or code: mcp.flowstudio.app, make.powerautomate.com and schema.management.azure.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Power Automate Build safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Power Automate Build use?

Power Automate Build is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Power Automate Build use?

About 4.3k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 17k tokens, read only when the agent opens those files.

What are the alternatives to Power Automate Build?

Skills that share tags, products or a category with Power Automate Build: Dv Connect (microsoft/Dataverse-skills, 243 stars), Flowstudio Power Automate Build (github/awesome-copilot, 40k stars), Flowstudio Power Automate MCP (github/awesome-copilot, 40k stars) and MCP Copilot Studio Server Generator (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Power Automate Build?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.