feat: submit pipefy-ipaas-usage-health

[danielgualberto]

Skill

Folder / Pasta: submissions/danielgualberto/pipefy-ipaas-usage-health/

What it does / O que faz: Org-wide iPaaS (Advanced Automations) usage/health briefing. Read-only. Separated from pipefy-ipaas (build) and pipefy-observability (native jobs / AI credits).

Contact / Contato

Email: danielgualberto@live.com

Name for credit / Nome para crédito: Daniel Gualberto

The problem it solves / O problema que resolve

CS/admins cannot see Advanced Automations health at org scope. Native observability does not cover iPaaS flow runs.

What it built when you ran it / O que ela construiu quando você rodou

Live hosted-MCP briefing: iPaaS-disabled pipe vs a test pipe (42 catalog tools, 2 DISABLED published flows, PRODUCTION FAILED empty, TESTING mixed FAILED/SUCCEEDED). Native 24h metrics = 0 runs (different unit). See EVIDENCE.md.

What you had to fix / O que você teve que corrigir

PRODUCTION status=FAILED looked healthy; the failure was TESTING. Documented the environment split. Kept real org/pipe ids out of the commit.

Checklist

• I provided a contact email in this description.
• I ran this skill in a real Pipefy organization.
• SKILL.md and EVIDENCE.md are both in the folder.
• The frontmatter name matches the folder name.
• No tokens, keys, real IDs, customer names, or personal data.
• I wrote this skill, and I agree it is published under Apache 2.0 with credit to me.

[adriannoes]

Thank you for taking part in MCP Builders, Daniel.

What we verified

We ran the read path of the skill against the hosted MCP server.

• Every tool and catalog entry named in the skill exists.
• The argument shapes matched the live schemas: flowRunId on run detail, environment defaulting to PRODUCTION, limit capped at 50, no date filter on the run listing, numeric or UUID organization id on the usage tools.
• The two edge branches behaved as written. A pipe with a workspace but no flows is classified as enabled but unused, and an organization with iPaaS disabled stops the iPaaS section and falls back to the native usage tools.

The skill covers something neither the iPaaS skill nor the observability skill in the toolkit does today: an organization-level view of Advanced Automations run health, with iPaaS runs, native automation counts and AI credits kept as separate units. The environment split you recorded after the first run (PRODUCTION looked healthy, the failures were in TESTING) is the type of finding a failure-modes table is for.

Suggestions, not blocking

1. The relative links to sibling skills and toolkit docs assume the file lives inside the toolkit tree, so none of them resolve in this repository. Absolute GitHub URLs or plain skill names would fix it.
2. The evidence tells the PRODUCTION versus TESTING story, but the screenshots show a flow list and one succeeded run. Pasting the two run-listing outputs side by side, plus the briefing the skill produced, would let a reader verify it.
3. LOG_SIZE_EXCEEDED is also a run status not covered by status=FAILED.

Next steps

Approved and accepted into the program. After we merge here, we will bring the skill into the official Pipefy AI Toolkit repository, adapted to its format and CI, referencing this pull request and crediting you as a contributor there. We will reach out by email about the details.