Pipefy Process Intelligence

Process Intelligence

Analyze existing pipes for improvement opportunities and implement them progressively. Investigate immediately. Diagnose with data. Improve progressively.

When to use

The user asks to analyze or improve an existing process:

• "Analyze my pipe"
• "How can I improve this process?"
• "Is this pipe optimized?"
• "Where are the bottlenecks?"

Not for: designing a new process from scratch → use skills/process-design/.

Prerequisites

• Pipe ID or name is known (or searchable via search_pipes).
• Read access to the pipe's cards and phase data.

Steps — investigation (Round 1)

1. Get pipe structure:

   MCP: get_pipe pipe_id=<id>

   Capture: phases, field count per phase, automation count.

2. Sample recent cards (last 30–50):

   MCP: get_cards pipe_id=<id> first=50 include_fields=true

   Look for: stale cards (no updates), cards stuck in early phases, phases with 0 cards.

3. Check automations:

   MCP: get_automations pipe_id=<id>

   Look for: phases with no automations (manual handoffs), repeated manual steps.

4. Check AI configuration:

   MCP: get_ai_agents repo_uuid=<PIPE_UUID>

   Look for: no AI agents despite manual categorization or triage patterns.

Diagnosis framework

Steps — improvement (Round 2+)

Each round focuses on 1–2 improvements; report results before proceeding.

Example: add an overdue automation

1. Identify the stalled phase and threshold (e.g., "Under Review" > 3 days).

2. Check automation events: get_automation_events

3. Create the automation:

   MCP: create_automation pipe_id=<id> name="Overdue Alert" trigger_event="card_overdue" actions='[{"type":"send_email","to":"assignee"}]'

4. Report: "Added overdue automation to 'Under Review' phase — triggers after 3 days and emails the assignee."

Example: add a field condition

1. Identify a field that should only show when another field has a specific value.

2. Create the condition:

   MCP: create_field_condition pipe_id=<id> phase_id=<phase_id> action="show" when='{"field_id":"<f1>","value":"Yes"}' fields='["<f2>"]'

Output format per round

## Analysis — [Pipe Name]

### Findings
- [Finding 1]: [evidence from tool calls]
- [Finding 2]: ...

### Implemented this round
- [Change 1]: [tool called + result]

### Next round (if approved)
- [Opportunity]: [proposed action]

Success criteria

• Each round produces a concrete visible change (new automation, field condition, phase cleanup).
• Card throughput improves in the affected phase within the next sprint.
• No improvement causes a regression (verify with get_pipe and get_cards after each round).

Failure modes

• get_cards returns empty: pipe may have no cards yet — analyze structure only and recommend first card creation.
• create_automation fails with unknown event: use get_automation_events to list valid triggers.
• User pushes back on automation: explain what the automation does in plain language before creating.

See also

• skills/automations/ — detailed automation creation guide.
• skills/ai-agents/ — add conversational agents for user-facing automation.
• skills/observability/ — check credit and execution data to quantify improvement impact.