Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ninihen1/power-automate-mcp-skills --skill power-automate-debuggit clone --depth 1 https://github.com/ninihen1/power-automate-mcp-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ninihen1/power-automate-mcp-skills/power-automate-debug)<a href="https://agentmods.dev/skills/ninihen1/power-automate-mcp-skills/power-automate-debug"><img src="https://agentmods.dev/badge/skills/ninihen1/power-automate-mcp-skills/power-automate-debug/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ninihen1/power-automate-mcp-skills/power-automate-debug"><img src="https://agentmods.dev/badge/skills/ninihen1/power-automate-mcp-skills/power-automate-debug.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00133 | $0.04992 |
| Opus 5 | $0.00067 | $0.02496 |
| Sonnet 5 | $0.00027 | $0.00998 |
| Haiku 4.5 | $0.00013 | $0.00499 |
Grade A, and why
power-automate-debug scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
import json, urllib.request This is a copy
89% identical to flowstudio-power-automate-debug — 42 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 495 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Power Automate Debugging with FlowStudio MCP
A step-by-step diagnostic process for investigating failing Power Automate cloud flows through the FlowStudio MCP server.
Real debugging examples: Expression error in child flow | Data entry, not a flow bug | Null value crashes child flow
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
list_skills/tool_searchfirst 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 diagnostic patterns — things tool schemas cannot tell you. If this document disagrees withtool_searchor a real API response, the API wins.
Python Helper
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
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago Changed · +2 lines 9b4eec11a616
- 12d ago First seen · 493 lines · 133 tokens per session scan A 1af315ddecfc
power-automate-debug is a skill published in the GitHub repository ninihen1/power-automate-mcp-skills (32 stars, last pushed 7d ago), licensed MIT. It adds 133 tokens to every session and 4,992 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 89% identical to flowstudio-power-automate-debug, differing in 42 lines, and is treated as a copy.
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