| name | pipefy-observability |
| description | Use this skill when the user wants to check AI agent logs, automation execution logs, org-level usage stats, AI credit consumption, or export automation job history. Covers 10 MCP tools.
|
| tags | ["pipefy","observability","logs","usage","credits","exports"] |
Observability
Monitor AI agent and automation execution, usage stats, credit consumption, and export job history. 10 MCP tools.
CLI status (v0.1): use MCP tools below. Observability Typer commands are planned for v0.3+.
Identifiers reference
| Concept | What tools expect | How to obtain |
|---|
| Pipe for AI agent logs | repo_uuid — the pipe UUID | get_pipe with numeric pipe_id; use pipe.uuid. |
| Automation for logs | automation_id — numeric | get_automations pipe_id=... |
| Org for usage stats | organization_id — numeric | Known from account setup or get_organization. |
Tools
| Tool (MCP) | CLI | Read-only | Purpose |
|---|
get_ai_agent_logs | — (CLI v0.3+) | Yes | Execution history for a specific AI agent. |
get_ai_agent_log_details | — (CLI v0.3+) | Yes | Single execution detail for an AI agent log entry. |
get_automation_logs | — (CLI v0.3+) | Yes | Execution history for an automation (by automation ID or pipe). |
get_automation_logs_by_repo | — (CLI v0.3+) | Yes | Automation logs filtered by pipe UUID. |
get_agents_usage | — (CLI v0.3+) | Yes | Org-level AI agent execution count and trends. |
get_automations_usage | — (CLI v0.3+) | Yes | Org-level automation execution stats. |
get_ai_credit_usage | — (CLI v0.3+) | Yes | AI credit consumption and remaining balance. |
export_automation_jobs | — (CLI v0.3+) | Yes | Trigger async export of automation job history. |
get_automation_jobs_export | — (CLI v0.3+) | Yes | Poll export job status (after export_automation_jobs). |
get_automation_jobs_export_csv | — (CLI v0.3+) | Yes | Download finished automation-jobs export as CSV text. |
Steps — diagnose a failing AI agent
-
Get the pipe UUID (not the numeric pipe ID):
MCP: get_pipe pipe_id=67890
Capture pipe.uuid from the response.
-
Fetch recent agent logs:
MCP: get_ai_agent_logs repo_uuid=<UUID> page=1
-
Identify the failed execution — look for status: failed entries.
-
Check credit usage if the agent stopped unexpectedly:
MCP: get_ai_credit_usage organization_id=123
-
Fix and re-enable — update the agent config (see skills/ai-agents/) and toggle status:
MCP: toggle_ai_agent_status agent_id=456
Steps — export automation history as CSV
-
Trigger the export:
MCP: export_automation_jobs organization_id=123 period="current_month"
-
Poll for completion:
MCP: get_automation_jobs_export export_id=<EXPORT_ID>
Repeat until status is finished or failed.
-
Fetch CSV text (when finished):
MCP: get_automation_jobs_export_csv export_id=<EXPORT_ID>
Success criteria
- Agent logs show execution timestamps and statuses.
- Credit usage shows remaining balance; no unexpected drops.
- CSV export downloads successfully and contains expected automation history.
Failure modes
get_ai_agent_logs returns empty: use the pipe UUID (e.g., abc123-...), not the numeric pipe ID. Get UUID from get_pipe.get_automation_jobs_export stays in processing: large exports take time. Wait at least 60 seconds between polls. If still processing after several minutes, retry the export trigger.- Credit usage shows 0 remaining: alert the user — AI features will stop working until credits are replenished. Escalate to the Pipefy admin.
See also
skills/ai-agents/ — create and configure AI agents.skills/automations/ — create and debug automation rules.
