pipefy-ai-agents

name	pipefy-ai-agents
description	Use this skill when the user wants to create, read, update, delete, or troubleshoot AI agents (conversational agents with behaviors). Covers 7 MCP tools including pre-flight validation. For traditional automations and AI automations, see skills/automations/.
tags	["pipefy","ai-agents","behaviors","conversational"]

AI Agents

Conversational AI agents attached to pipes. Each agent has an agent-level instruction and 1–5 behaviors, each with its own trigger event, prompt, and actions. 7 MCP tools.

For traditional automations and AI automations (prompt-driven), see skills/automations/pipefy-automations/SKILL.md.

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Tools

Tool (MCP)	CLI	Read-only	Purpose
get_ai_agents	pipefy agent list	Yes	List AI agents for a pipe (repo_uuid = pipe UUID, not numeric id).
get_ai_agent	pipefy agent get	Yes	Full agent config including behaviors.
create_ai_agent	pipefy agent create	No	Create a new conversational agent.
update_ai_agent	pipefy agent update	No	Full-replace (not patch). Always send complete behaviors.
delete_ai_agent	pipefy agent delete	No	(Two-step destructive)
toggle_ai_agent_status	pipefy agent toggle	No	Enable/disable the agent (e.g. --inactive).
validate_ai_agent_behaviors	pipefy agent validate-behaviors	Yes	Pre-flight check before create/update.

Execution logs live in skills/observability/ (get_ai_agent_logs, get_ai_agent_log_details).

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Creation workflow (discover → validate → create → verify)

Never guess event IDs, phase IDs, action types, or field IDs.

1 — Get pipe metadata

Call get_pipe(pipe_id) and extract:

• uuid → use as repo_uuid in all AI-agent tools.
• phases[].id / phases[].name → needed for move_card actions.
• Fields via get_start_form_fields(pipe_id) and/or get_phase_fields(phase_id) → needed for update_card actions.

2 — Check existing agents

get_ai_agents(repo_uuid) to avoid duplicates. To modify an existing agent, use update_ai_agent (not create). For full config, use get_ai_agent(uuid).

3 — Discover valid trigger events

get_automation_events(pipe_id). Common events:

Event (event_id value)	event_params required	Example
card_created	None	{}
card_moved	{"to_phase_id":"<phase_id>"}	Fires only when card enters that phase.
field_updated	{"triggerFieldIds":["<field_id>", ...]}	Fires only when those fields change.
manually_triggered	None	User clicks button on card.

For card_moved and field_updated, you MUST include event_params. Omitting it makes the behavior fire on every occurrence.

4 — Discover valid action types

get_automation_actions(pipe_id). Inside actionsAttributes:

Action (actionType value)	metadata required
update_card	pipeId + fieldsAttributes with inputMode
move_card	destinationPhaseId
create_card	pipeId + fieldsAttributes
create_connected_card	pipeId + fieldsAttributes (requires pipe relation)

5 — Build the behavior dict

{
  "name": "<descriptive name>",
  "event_id": "<from step 3>",
  "event_params": {},
  "actionParams": {
    "aiBehaviorParams": {
      "instruction": "<prompt for the AI when this event fires>",
      "actionsAttributes": [
        { "name": "<action label>", "actionType": "<from step 4>", "metadata": { } }
      ]
    }
  }
}

• Each behavior MUST have at least one action in actionsAttributes.
• Maximum 5 behaviors per agent.
• The MCP tool auto-injects referenceId and %{action:<uuid>} placeholders — do NOT generate these yourself.
• inputMode: "fill_with_ai" lets the AI decide the value. Omit inputMode and set value for fixed values.
• For update_card: set destinationPhaseId: "" when not moving the card.

Example identifiers (fictional)

Use real values from get_pipe / get_start_form_fields for your org. Placeholders below match unit-test fixtures in this repo. The syntax matters (pipeId, fieldId, %{field:<internal_id>}, inputMode) — the example digits do not; substitute each pipe's numeric internal_id and phase id.

Role	Example value
Pipe (numeric repo id)	987654321
Field internal_id	900000101
Destination phase (move_card)	900000201
Target pipe (create_card)	900000301

Metadata examples

// update_card
{ "pipeId": "987654321", "destinationPhaseId": "", "fieldsAttributes": [{ "fieldId": "900000101", "inputMode": "fill_with_ai", "value": "" }] }

// move_card
{ "destinationPhaseId": "900000201", "pipeId": "", "fieldsAttributes": [] }

// create_card
{ "pipeId": "900000301", "fieldsAttributes": [{ "fieldId": "title", "inputMode": "fill_with_ai", "value": "" }] }

6 — Validate (recommended for complex behaviors)

validate_ai_agent_behaviors(pipe_id, behaviors) checks:

• Field IDs exist in the pipe
• Phase IDs exist
• Pipe relations exist for create_connected_card
• Action types are valid
• Behavior structure passes Pydantic validation
• Service-account membership on cross-pipe targets when PIPEFY_SERVICE_ACCOUNT_IDS is set
• Field IDs are checked against start-form and phase fields, accepting both slug id and numeric internal_id. Placeholders like %{field:<slug>} or %{field:<internal_id>} are validated but not rewritten at this step.

7 — Create the agent

create_ai_agent with name, repo_uuid, instruction, and behaviors. One-call creation is preferred — avoids partial agent shells. Agents are active by default.

On create/update, slug fieldId values are resolved to numeric internal_id, %{field:<slug>} is rewritten to %{field:<internal_id>}, and referencedFieldIds is auto-populated when applicable.

8 — Handle responses

• Success with agent_uuid → done.
• Partial failure (UUID returned, behaviors rejected) → call update_ai_agent with that UUID. Do NOT create a second agent.
• Failure without UUID → validation or API error. Trust the hint text in the enriched error.

9 — Verify

get_ai_agent(uuid) to confirm behaviors match expectations.

---

Token normalization & slug resolution

Instructions accept five token aliases — all normalize to canonical %{field:<internal_id>}:

Form	Behavior
%{<internal_id>}	Canonical short form.
{<internal_id>}	Bare; auto-prefixed with %.
{field:<internal_id>}	Bare-with-prefix; auto-%.
{field:<slug>}	Bare slug; resolved to numeric when behavior action carries pipeId.
%{field:<internal_id>}	Canonical full form.

%{field:<slug>} is rewritten to %{field:<internal_id>} when an action in the behavior supplies pipeId. If the Pipefy UI shows plain text instead of chips in token slots, the payload probably still has non-canonical tokens.

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Template params / placeholders

Per behavior you can pass template_params (or placeholders) with str → str values and use {{name}} in any string (instruction, metadata IDs, etc.). Optionally set instruction_template instead of aiBehaviorParams.instruction — the tool interpolates and writes the final instruction before the API call. These keys are stripped before validation.

{
  "name": "Classify card",
  "event_id": "card_created",
  "instruction_template": "Read {{field_ref}} and classify the card.",
  "template_params": { "field_ref": "%{field:900000101}" },
  "actionParams": {
    "aiBehaviorParams": {
      "actionsAttributes": [
        {
          "name": "Fill classification",
          "actionType": "update_card",
          "metadata": { "pipeId": "{{pipe}}", "fieldsAttributes": [{ "fieldId": "{{class_field}}", "inputMode": "fill_with_ai", "value": "" }] }
        }
      ]
    }
  },
  "placeholders": { "pipe": "987654321", "class_field": "900000101" }
}

template_params and placeholders merge (placeholders wins on conflict).

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Naming differences (UI vs API)

Pipefy UI	API / Tool field
Description (agent creation step 1)	instruction (agent-level)
Instruction / Prompt (per behavior)	actionParams.aiBehaviorParams.instruction
Pipe UUID	repo_uuid (from get_pipe().uuid, NOT the numeric id)

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Success criteria

• get_ai_agent returns the agent with status: active.
• validate_ai_agent_behaviors reports no errors before creation.
• Agent appears in the Pipefy UI under the pipe's AI settings.

Failure modes

• update_ai_agent is full-replace, not patch. Fetch existing behaviors with get_ai_agent first, merge, then update — otherwise existing behaviors are silently dropped.
• Behavior save is all-or-nothing (RECORD_NOT_SAVED). One invalid behavior rejects the entire list. The MCP tool auto-validates the payload on failure; if structurally correct, the error indicates a pipe-level restriction (not your payload). Inform the user this pipe does not support AI agent behaviors and suggest alternatives.
• Partial-failure recovery. If create_ai_agent returns a UUID but reports failure, call update_ai_agent with that UUID. Do NOT create a second agent.
• Cross-pipe PERMISSION_DENIED. Behaviors with create_connected_card or cross-pipe create_card require the service account to be a member of both source and destination pipes. validate_ai_agent_behaviors catches this when PIPEFY_SERVICE_ACCOUNT_IDS is set; otherwise the API returns bare PERMISSION_DENIED. Recovery: get_pipe_members + invite_members on the destination pipe.
• Phase transition rule on move_card. Destination must be reachable from the source phase (cards_can_be_moved_to_phases). Both validate_ai_agent_behaviors and create_ai_agent / update_ai_agent enrich this error with valid_destinations and a hint that transition rules are editable in the Pipefy UI only.
• Maximum 5 behaviors per agent. Adding a 6th rejects the whole save.
• Ghost agents. An agent listed by get_ai_agents may return "Agent not found" on get_ai_agent — a Pipefy backend artifact, persists across sessions, do not retry.
• GraphQL error hints. When a dedicated read tool returns permission-denied or not-found, the error.message may cite concrete tools (e.g. "Use 'get_ai_agents' to list agents..."). Trust the hint; don't improvise alternative flows.
• Validation rejections. Common issues: invalid trigger_event, prompt too long, missing required action config. Read the errors field per behavior.
• delete_ai_agent first call returns preview. Expected — show preview to user, then call with confirm=true.

See also

• skills/automations/pipefy-automations/SKILL.md — traditional automations and AI automations (different from AI agents).
• skills/observability/pipefy-observability/SKILL.md — agent execution logs and credit usage.
• skills/introspection/pipefy-introspection/SKILL.md — Recipe 2 inspects full behavior config via execute_graphql.