pipefy-process-intelligence

name	pipefy-process-intelligence
description	Use this skill when the user wants to analyze an existing pipe for improvement opportunities — automation gaps, manual bottlenecks, missing AI agents, field conditions, or adjacent processes. Acts as a process analyst: investigates, diagnoses, and improves the pipe in progressive rounds — each round delivers visible results.
tags	["pipefy","process-intelligence","optimization","automation","analysis"]

Process Intelligence

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

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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/.

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Prerequisites

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

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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.

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Diagnosis framework

Signal	Opportunity
Cards stuck in a phase for >7 days	Add due date field + overdue automation
Phase transitions always done by same person	Automate the transition condition
Fields never filled in certain phases	Remove or make optional
Same comment posted repeatedly	AI agent to auto-post based on trigger
No automation between intake and first action	Add "notify assignee" automation on card creation
Large field count on start form	Move optional fields to later phases
Phases with 0 cards over 90 days	Consider removing or merging phases

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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>"]'

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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]

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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.