Official agent skill

Flowstudio Power Automate Build

by github in github/awesome-copilot

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

OfficialMITAuto-check passedAgent Workflows

Install Flowstudio Power Automate Build

skills CLI
$ npx skills add github/awesome-copilot --skill flowstudio-power-automate-build -a claude-code

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

GitHub CLI
$ gh skill install github/awesome-copilot flowstudio-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/github/awesome-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/flowstudio-power-automate-build .claude/skills/flowstudio-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
flowstudio-power-automate-build
GitHub stars
40k
Used in
2 other repos
Token cost
~5k tokens
SKILL.md length
1,331 words
Files
7 (incl. references)
Skills in repo
417
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 7 steps: Load the Current Build Tools → Safety Check: Does the Flow Already Exist? → Obtain Connection References → …
  • Tasks that involve MCP servers
  • SKILL.md covers Source of Truth, Python Helper, 0. Load the Current Build Tools and 1. Safety Check: Does the Flow…, plus 8 more sections
  • Reaches mcp.flowstudio.app and schema.management.azure.com; needs MCP_TOKEN

What it does

Flowstudio Power Automate Build is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. Your agent constructs flow definitions, wires connections, deploys, and tests — all via MCP without opening the portal. 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…

Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `references/action-patterns-connectors.md`, `references/action-patterns-core.md` and `references/action-patterns-data.md`).

It sits in Agent Workflows, covering MCP servers. It works with Model Context Protocol and Power Automate. The repository describes itself as: Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. The licence is MIT.

When your agent uses it

  • Tasks that involve MCP servers

Example prompts

  • “/flowstudio-power-automate-build”

Requirements

  • Python 3
  • A credential in MCP_TOKEN
  • A credential in YOUR_JWT_TOKEN

Workflow steps

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

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

What it can do on your machine

Read from SKILL.md and the folder at commit 727ff2e. 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
    • 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

Flowstudio Power Automate Build loads about 5k tokens when it runs, and up to ~22k if it reads all its reference files. Until then it costs about 153 tokens; SKILL.md has 1,331 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~153
When it runs · the whole SKILL.md, loaded when a task matches
~5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~22k

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 github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 1,331 words, ~4,973 tokens.

Download SKILL.mdSave it as .claude/skills/flowstudio-power-automate-build/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
flowstudio-power-automate-build
description
Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. Your agent constructs flow definitions, wires connections, deploys, and tests — all via MCP without opening the portal. 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 flowstudio-power-automate-mcp skill for connection setup. Subscribe at https://mcp.flowstudio.app

Workflow:

  1. Load current build tools.
  2. Check for an existing flow.
  3. Resolve connection references.
  4. Build the definition.
  5. Deploy.
  6. Verify.
  7. Test.

Source of Truth

Always call list_skills / tool_search first to confirm available tool names and parameter schemas. Tool names and parameters may change between server versions. This skill covers response shapes, behavioral notes, and build patterns — things tool schemas cannot tell you. If this document disagrees with tool_search 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

0. Load the Current Build Tools

For a brand-new flow, load the server's create-flow bundle. For editing an existing flow, load build-flow. This keeps the agent aligned with the MCP server's current schema before constructing JSON.

python
schemas = mcp("tool_search", query="skill:create-flow")
# Includes list_live_environments, list_live_connections,
# describe_live_connector, get_live_dynamic_options, update_live_flow.

If you need a tool outside the bundle, load it explicitly:

python
mcp("tool_search", query="select:get_live_dynamic_properties")

1. Safety Check: Does the Flow Already Exist?

Always look before you build to avoid duplicates:

python
results = mcp("list_live_flows",
    environmentName=ENV,
    mode="owner",
    search="My New Flow",
    top=20)

# list_live_flows returns { "flows": [...], "mode": "...", ... }
matches = [f for f in results["flows"]
           if "My New Flow".lower() in f["displayName"].lower()]

if len(matches) > 0:
    # Flow exists — modify rather than create
    FLOW_ID = matches[0]["id"]   # plain UUID from list_live_flows
    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

For very large environments, list_live_flows may return a continuation URL. Pass it back as continuationUrl with the same mode to retrieve the next batch. Use mode="admin" only when the user needs all environment flows and the MCP identity has admin rights.


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 — Find active connections
python
conns = mcp("list_live_connections", environmentName=ENV)
active = [c for c in conns["connections"]
          if c["statuses"][0]["status"] == "Connected"]
conn_map = {c["connectorName"]: c["id"] for c in active}

For a known connector, pass search to reduce output and get paste-ready connectionReferenceTemplate and hostTemplate values:

python
sp_conns = mcp("list_live_connections",
    environmentName=ENV,
    search="shared_sharepointonline")
2b — Determine which connectors the flow needs

Common connector API names: SharePoint shared_sharepointonline, Outlook shared_office365, Teams shared_teams, Approvals shared_approvals, OneDrive shared_onedriveforbusiness, Excel shared_excelonlinebusiness, Dataverse shared_commondataserviceforapps, Forms shared_microsoftforms.

Flows that need no connectors, such as Recurrence + Compose + HTTP only, can omit connectionReferences.

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 missing:
    # STOP: connections require browser OAuth consent.
    # Ask the user to create the missing connector connections in the
    # selected environment, then re-run list_live_connections.
    raise Exception(f"Missing active connections: {missing}")
2d — Build the connectionReferences block
python
connection_references = {}
host_templates = {}
for connector in connectors_needed:
    c = next(c for c in active if c["connectorName"] == connector)
    connection_references[connector] = c.get("connectionReferenceTemplate") or {
        "connectionName": c["id"],   # the connection id from list_live_connections
        "source": "Invoker",
        "id": f"/providers/Microsoft.PowerApps/apis/{connector}"
    }
    host_templates[connector] = c.get("hostTemplate") or {
        "connectionName": connector
    }

In Step 3 action JSON, inputs.host.connectionName must be the map key such as shared_teams, not the GUID. The GUID belongs only inside the connectionReferences[connector].connectionName value. If an existing flow uses the same connectors, you may also copy its properties.connectionReferences from get_live_flow.


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.

Discover connector operations before guessing JSON

For connector-backed triggers/actions, prefer the live connector describer over hand-written shapes. It can return authored hints, canonical examples, variant keys, inputs/outputs, and dynamic metadata pointers.

python
# Search across connectors when you know the user's intent but not the API.
matches = mcp("describe_live_connector",
    environmentName=ENV,
    search="send email",
    top=5)

# Describe a specific operation before copying an exampleDefinition.
op = mcp("describe_live_connector",
    environmentName=ENV,
    connectorName="shared_office365",
    operationId="SendEmailV2")
print(op.get("hint"))

When an operation has multiple authored variants, request the variant the flow needs:

python
teams_chat = mcp("describe_live_connector",
    environmentName=ENV,
    connectorName="shared_teams",
    operationId="PostMessageToConversation",
    variant="flowbot_chat")

When the operation description says a parameter has dynamic options or dynamic properties, call the indicated next tool:

python
sp_op = mcp("describe_live_connector",
    environmentName=ENV,
    connectorName="shared_sharepointonline",
    operationId="GetItems")

sites = mcp("get_live_dynamic_options",
    environmentName=ENV,
    connectorName="shared_sharepointonline",
    connectionName=conn_map["shared_sharepointonline"],
    operationId="GetItems",
    parameterName="dataset",
    dynamicMetadata=sp_op["dynamicParameters"]["dataset"])

fields = mcp("get_live_dynamic_properties",
    environmentName=ENV,
    connectorName="shared_sharepointonline",
    connectionName=conn_map["shared_sharepointonline"],
    operationId="GetItems",
    parameterName="item",
    parameters={"dataset": "<site-url>", "table": "<list-id>"},
    dynamicMetadata=sp_op["dynamicProperties"]["item"])

Use dynamic options for dropdown IDs such as SharePoint sites/lists and Teams teams/channels. Use dynamic properties for schema/field shapes such as SharePoint list item columns.


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
definition["description"] = "Weekly SharePoint → Teams notification flow, built by agent"

result = mcp("update_live_flow",
    environmentName=ENV,
    # flowName omitted → creates a new flow
    definition=definition,
    connectionReferences=connection_references,
    displayName="Overdue Invoice Notifications"
)

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
definition["description"] = (
    "Updated by agent on " + __import__('datetime').datetime.utcnow().isoformat()
)

result = mcp("update_live_flow",
    environmentName=ENV,
    flowName=FLOW_ID,
    definition=definition,
    connectionReferences=connection_references,
    displayName="My Updated Flow"
)

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.

⚠️ Flow description lives at definition["description"]. The current server appends #flowstudio-mcp for usage tracking. Do not pass a top-level description argument unless tool_search shows one in the active schema.

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

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"
# If state is "Stopped", use set_live_flow_state — NOT update_live_flow
# mcp("set_live_flow_state", environmentName=ENV, flowName=FLOW_ID, state="Started")

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

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.

Show full SKILL.md (530 more words)Show less
Updated flows (have prior runs) — ANY trigger type

Use resubmit_live_flow_run first. It works for EVERY trigger type — Recurrence, SharePoint, connector webhooks, Button, and HTTP. It replays the original trigger payload. Do NOT ask the user to manually trigger the flow or wait for the next scheduled run.

python
runs = mcp("get_live_flow_runs", environmentName=ENV, flowName=FLOW_ID, top=1)
if runs:
    # Works for Recurrence, SharePoint, connector triggers — not just HTTP
    result = mcp("resubmit_live_flow_run",
        environmentName=ENV, flowName=FLOW_ID, runName=runs[0]["name"])
    print(result)   # {"resubmitted": true, "triggerName": "..."}
HTTP, Button, and PowerApps flows — custom test payload

Only use trigger_live_flow when you need to send a different payload than the original run. For verifying a fix, resubmit_live_flow_run is better because it uses the exact data that caused the failure.

python
defn = mcp("get_live_flow", environmentName=ENV, flowName=FLOW_ID)
triggers = defn["properties"]["definition"]["triggers"]
manual = next(iter(triggers.values()))
print("Expected body:", manual.get("inputs", {}).get("schema"))

result = mcp("trigger_live_flow",
    environmentName=ENV, flowName=FLOW_ID,
    body={"name": "Test", "value": 1})
print(f"Status: {result['responseStatus']}, via: {result['invocation']}")
print(result.get("warning"))   # set when a required input was missing: the run still ran, with null
Brand-new non-HTTP flows

A brand-new Recurrence flow needs no workaround: deploy it, then run it immediately with trigger_live_flow and no body — same as the portal's "Run flow" button. A body is refused; scheduled triggers take no inputs.

A brand-new connector-triggered flow (SharePoint, webhooks) has no prior runs and cannot fire without a real source event. Deploy with a temporary HTTP trigger, test the actions, then swap to the production trigger:

python
production_trigger = definition["triggers"]
definition["triggers"] = {
    "manual": {"type": "Request", "kind": "Http", "inputs": {"schema": {}}}
}
result = mcp("update_live_flow", environmentName=ENV,
    flowName=FLOW_ID,       # omit if creating new
    definition=definition, connectionReferences=connection_references,
    displayName="Overdue Invoice Notifications")
FLOW_ID = FLOW_ID or result["flowName"]

mcp("trigger_live_flow", environmentName=ENV, flowName=FLOW_ID,
    body={"sample": "payload"})
runs = mcp("get_live_flow_runs", environmentName=ENV, flowName=FLOW_ID, top=1)
if runs[0]["status"] == "Failed":
    err = mcp("get_live_flow_run_error",
        environmentName=ENV, flowName=FLOW_ID, runName=runs[0]["name"])
    raise Exception(err["failedActions"][-1])

definition["triggers"] = production_trigger
mcp("update_live_flow", environmentName=ENV, flowName=FLOW_ID,
    definition=definition, connectionReferences=connection_references)

The trigger is only the entry point; testing through HTTP still exercises the same actions. If actions use triggerBody() or triggerOutputs(), pass a representative body shaped like the production trigger payload.


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 scheduleCall set_live_flow_state with state: "Started" — do not use update_live_flow for state changes
Teams "Chat with Flow bot" recipient as object400 GraphUserDetailNotFoundUse plain string with trailing semicolon (see below)
Copilot/Skills flow not in a solutionCopilot Studio may not discover it as an agent toolAfter deploy, call add_live_flow_to_solution with the target solutionId
Button/Skills trigger used for MCP testingRuns even when a required input is missing (null)Pass inputs in trigger_live_flow body; on warning, cancel and retry with the full body
Connector action missing metadata.operationMetadataIdDesigner/run-only UI can behave inconsistentlyPreserve existing IDs; add stable GUIDs for new connector actions
Placeholder Excel scriptIdDynamic validation fails at save timeResolve the real Office Script ID before deploying
SharePoint PatchItem omits required fieldsSave can fail even if the field is not changingEcho unchanged required fields such as item/Title
Copilot Studio connector calls a draft agentConnector invocation can fail or hit stale behaviorPublish the agent before testing/resubmitting the flow
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

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

© github, 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 6 other files (references) in skills/flowstudio-power-automate-build of github/awesome-copilot.

  • SKILL.md
  • 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 727ff2e

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Flowstudio 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.

Flowstudio Power Automate Build compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Flowstudio Power Automate Build this skillgithub/awesome-copilot40k2 repos~5kAutomated safety check: PassMIT
Dv Connectmicrosoft/Dataverse-skills2411 repos~5kAutomated safety check: NotesMIT
Microsoft Docsmicrosoft/ai-agents-for-beginners77k—~1.5kAutomated safety check: PassMIT
Power Automate MCPLeoYeAI/openclaw-master-skills2.2k—~4.4kAutomated safety check: PassMIT
Power Automate BuildLeoYeAI/openclaw-master-skills2.2k—~4.3kAutomated safety check: PassMIT
Power Automate MCPhashgraph-online/awesome-codex-plugins1.2k—~3.4kAutomated safety check: PassApache-2.0

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    github/awesome-copilot

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Questions about Flowstudio Power Automate Build

What does Flowstudio Power Automate Build do?

Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server. Flowstudio Power Automate Build is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio MCP server.

When should I use Flowstudio Power Automate Build?

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

How do I install Flowstudio Power Automate Build in Claude Code?

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

How do I install Flowstudio Power Automate Build in Codex?

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

Can I use Flowstudio 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 github/awesome-copilot --skill flowstudio-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/flowstudio-power-automate-build, .gemini/skills/flowstudio-power-automate-build, .github/skills/flowstudio-power-automate-build and .opencode/skills/flowstudio-power-automate-build in your project.

What does Flowstudio Power Automate Build need to run?

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

Does Flowstudio Power Automate Build access the network?

SKILL.md names 2 domains. In commands or code: mcp.flowstudio.app 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 Flowstudio 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 Flowstudio Power Automate Build use?

Flowstudio 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 Flowstudio Power Automate Build use?

About 5k tokens (SKILL.md is roughly 20k 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 Flowstudio Power Automate Build?

Skills that share tags, products or a category with Flowstudio Power Automate Build: Dv Connect (microsoft/Dataverse-skills, 241 stars), Microsoft Docs (microsoft/ai-agents-for-beginners, 77k stars), Power Automate MCP (LeoYeAI/openclaw-master-skills, 2.2k stars) and Power Automate Build (LeoYeAI/openclaw-master-skills, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Flowstudio Power Automate Build?

github (a GitHub organization, an official publisher) maintains it in github/awesome-copilot, which has 39,748 GitHub stars. The repository holds 417 skills in this directory. The repository was last updated on October 7, 2026.

Source: github/awesome-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.