Files
windmill/system_prompts/auto-generated/flow.md
3cba8a7e4c feat: add an AI decision flow step (TypeSafe's Jev, Cloudflare's Clef) (#11474)
* feat: add an AI decision flow step on TypeSafe's Jev

An `aidecision` step asks TypeSafe's Jev typed questions (choice, score,
yes/no) about a state and returns calibrated answers. It is a plain step:
a flow routes on the answers with a Branch to one after it, which the
editor builds and keeps in step with the questions. It can also be an AI
agent tool, where the calling model supplies the state.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

* fix: read single-quoted branch conditions and flag branches on a removed question

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

* fix: route decision tools by their tag and keep structured questions as JSON

The questions editor writes only on an edit, so opening a step leaves its
value untouched, and questions the cards cannot hold stay in a JSON editor.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

* fix: re-pick the questions editor mode when the value is replaced from elsewhere

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

* fix: keep the questions JSON editor's text in step with the value

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

* fix: recreate the questions JSON editor when the value is replaced from elsewhere

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

* feat: run AI decisions on Cloudflare's Clef as well as TypeSafe's Jev

A `cloudflare` provider kind reads the hub's `cloudflare` resource (token and
account id), calls the model's Workers AI URL, and unwraps Workers AI's
`result` envelope. Like TypeSafe, it serves decision steps only.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* feat: branch from each AI decision question, and align its editor with the brand guidelines

"Branch on this question" now sits in each choice question's card, which also
links to the Branch to one that routes it and flags options it misses or
branches it no longer matches. Labels, errors, cards and icons follow the form
guidelines and the Branch to one's cards.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* feat: branch on an AI decision from its graph node

A decision with a choice question nothing branches on yet shows a button beside
its node that inserts the Branch to one, as its question card does.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: resolve Cloudflare resources in the AI proxy, and use the design-system button on the graph

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: put the decision_inputs test's doc comment back on it

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* chore: regenerate the flow schema in prompts and the chat after the AiDecision description edit

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* feat: switch AI decision questions between the form and JSON

JSON is always available; the form is offered whenever its cards can hold the
questions, and a value they cannot hold still opens in JSON.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: show step ids as badges and use the JSON toggle of the run forms

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: quote option names in the AI decision branch alerts

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* feat: remove stale branches from the AI decision question card

An empty branch is removed directly; one with steps asks first, naming how many
steps go with it.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* feat: branch on yes/no AI decision questions, and test a decision step from the AI chat

A yes/no question branches like a choice: "Branch on this question" writes one
"yes" branch on `noul >= 0.5`, with the default as "no", and the helper still
reads it once the threshold is tuned. The AI chat's step test runs a decision
alone as a one-step preview, taking the state the chat passes.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: record removing several stale branches as one undo step

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: name the typesafe resource type TypeSafe

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: store TypeSafe as the typesafe resource type's display name, not in the word map

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: leave the typesafe and cloudflare resource types to the hub instead of seeding them

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* docs(AGENTS): resource types ship through the hub, not migrations

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: show the questions JSON format beside the JSON toggle

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: give the questions JSON format in the field's description

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: style the decision's graph branch button like Add branch

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: show the questions JSON format only in JSON mode

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* feat: show each question's branching under the questions JSON editor

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: drop the redundant In JSON prefix from the questions format

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: shorten the decision state's description and show an example as its placeholder

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: escape a schema placeholder before the JSON editor renders it as HTML

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* fix: give the decision state's placeholder a text and an object example

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019sEUVZVYBjkzkaVkjbFeAL

* chore: update ee-repo-ref to 154cbccb6b8d47bf662b5507882917b5933d5a45

This commit updates the EE repository reference after PR #839 was merged in windmill-ee-private.

Previous ee-repo-ref: eaf38c1388f3cc5bece163404fffa959ede8cae0

New ee-repo-ref: 154cbccb6b8d47bf662b5507882917b5933d5a45

Automated by sync-ee-ref workflow.

---------

Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
Co-authored-by: windmill-internal-app[bot] <windmill-internal-app[bot]@users.noreply.github.com>
2026-10-05 14:23:34 +00:00

67 KiB

Windmill Flow Building Guide

OpenFlow Schema

The OpenFlow schema (openflow.openapi.yaml) is the source of truth for flow structure. Refer to OPENFLOW_SCHEMA for the complete type definitions.

Reserved Module IDs

  • failure - Reserved for failure handler module
  • preprocessor - Reserved for preprocessor module
  • Input - Reserved for flow input reference

Hard Structural Rules

These are strict Windmill schema rules. Follow them exactly.

  • value.modules is only for normal sequential steps
  • value.preprocessor_module and value.failure_module are special top-level fields inside value, not entries in value.modules
  • If a flow needs a preprocessor, create value.preprocessor_module with id: preprocessor
  • If a flow needs a failure handler, create value.failure_module with id: failure
  • Do NOT create regular modules inside value.modules named preprocessor or failure
  • preprocessor_module and failure_module only support script or rawscript
  • preprocessor_module runs before normal modules and cannot reference results.*
  • failure_module can use the error object with error.message, error.step_id, error.name, and error.stack

Correct shape:

value:
  preprocessor_module:
    id: preprocessor
    value:
      type: rawscript
      ...
  failure_module:
    id: failure
    value:
      type: rawscript
      ...
  modules:
    - id: process_event
      value:
        type: rawscript
        ...

Incorrect shape:

value:
  modules:
    - id: preprocessor
      ...
    - id: process_event
      ...
    - id: failure
      ...

Module ID Rules

  • Must be unique across the entire flow
  • Use underscores, not spaces (e.g., fetch_data not fetch data)
  • Use descriptive names that reflect the step's purpose

AI Agent Modules

An aiagent module runs an LLM that can call tools. Each entry of value.tools is a module-shaped object with an extra value.tool_type: flowmodule for a script/flow tool, mcp for an MCP server tool, websearch for web search.

{
  "id": "support_agent",
  "summary": "AI agent for customer support",
  "value": {
    "type": "aiagent",
    "input_transforms": {
      "provider": {
        "type": "static",
        "value": { "kind": "openai", "resource": "$res:f/ai_providers/openai", "model": "gpt-4o" }
      },
      "output_type": { "type": "static", "value": "text" },
      "user_message": { "type": "javascript", "expr": "flow_input.query" },
      "system_prompt": { "type": "static", "value": "You are a helpful assistant." }
    },
    "tools": [
      {
        "id": "search_docs",
        "summary": "search_documentation",
        "description": "Search the product documentation. Use it whenever the user asks how a feature works.",
        "value": {
          "tool_type": "flowmodule",
          "type": "rawscript",
          "language": "bun",
          "content": "export async function main(query: string) { return ['doc1', 'doc2']; }",
          "input_transforms": { "query": { "type": "static", "value": "" } }
        }
      }
    ]
  }
}
  • provider is an object, not a bare resource string: { "kind": <provider kind>, "resource": "$res:<path>", "model": <model id> }. Required unless the module links to a saved agent through value.agent. Static is right for a flow run from a form; a chat flow wires its fields to flow inputs instead — see below

Chat-Mode Flows

A flow with value.chat_input_enabled: true is run from a chat instead of a form: the composer sends one message per turn and renders the conversation. It needs a required user_message string input, read by the agent. Any other flow input the composer does not edit itself is asked for under Configure inputs.

A static provider gives a chat that cannot change its model. Feed it from flow inputs instead, either way round: one input carrying the whole object ("expr": "flow_input.model_config") makes every field editable, or wire it field by field to fix some and expose others. A field the chat can write becomes a control in the composer — a provider picker, a model list, a thinking control — and a field left static is fixed, with no control drawn for it. kind is the one exception: the composer writes it only together with resource, since a provider is picked as a pair, so a kind input wired on its own stays askable under Configure inputs and nothing the run needs becomes unreachable.

{
  "id": "chat_agent",
  "value": {
    "type": "aiagent",
    "input_transforms": {
      "provider": {
        "type": "javascript",
        "expr": "({ kind: 'anthropic', resource: '$res:f/ai/claude', model: flow_input.model, reasoning_effort: flow_input.thinking })"
      },
      "user_message": { "type": "javascript", "expr": "flow_input.user_message" },
      "user_attachments": { "type": "javascript", "expr": "flow_input.files" },
      "memory": { "type": "static", "value": { "kind": "compaction" } },
      "streaming": { "type": "static", "value": true },
      "output_type": { "type": "static", "value": "text" }
    },
    "tools": []
  }
}
  • Wiring field by field means one object literal whose values are literals or bare flow_input.x references. A spread, a call or a computed key leaves the composer unable to tell which input feeds which field, so it offers no control at all — a bare flow_input.x for the whole object is read instead as that one input carrying every field
  • memory is what lets the agent see earlier turns; without it every message starts from nothing
  • streaming on makes the answer and its thinking appear token by token instead of all at once
  • user_attachments points at a flow input typed as an array of s3 objects ({ "type": "array", "items": { "type": "object", "resourceType": "s3object" } }), so files sent with a message reach the agent
  • Running one needs a memory_id query parameter — not a flow argument — naming the conversation the turn belongs to: a fresh UUID starts one, reusing a UUID continues it. The chat supplies it itself; a run driven any other way has to pass it or the server refuses the job

Tool Naming Rules

These rules cover flowmodule tools, the ones the agent calls by name. A websearch tool's summary is a plain label (Web Search), and an mcp tool exposes the MCP server's own tool names, so neither is name-checked at all — leave those summaries as they are.

  • A flowmodule tool's summary is the name the agent calls it by, not a human label. Put the human-readable explanation in description
  • summary must match ^[a-zA-Z0-9_]+$: letters, numbers and underscores only. No spaces, dashes, dots or accents — search_documentation, never Search documentation
  • Always set summary. It must be unique among that agent's tools, and must not be one of the reserved ids (do, bg, ctx, state, if, else, for, delete, while, new, in, failure, preprocessor, as, Input, Result, Trigger)
  • A tool name outside that character set fails any run that offers the tool to the agent, with Invalid tool name. The flow write tools refuse such a name.
  • Tool id follows the same rules as any module ID — unique across the flow, underscores not spaces
  • description is optional free text telling the agent when and how to call the tool. Set it whenever the name alone does not make that obvious; it overrides the description derived from the underlying script

AI Decision Modules

An aidecision module asks a decision model (TypeSafe's Jev or Cloudflare's Clef) typed questions about a state and answers each with calibrated probabilities instead of text. Prefer it over an aiagent when the step is a judgment (classify, route, score or a yes/no check) that needs no tools and no free text: it is faster, cheaper, and its answers have a fixed shape.

{
  "id": "triage",
  "summary": "Classify the ticket",
  "value": {
    "type": "aidecision",
    "input_transforms": {
      "provider": {
        "type": "static",
        "value": { "kind": "typesafe", "resource": "$res:f/ai/typesafe", "model": "jev-latest" }
      },
      "state": { "type": "javascript", "expr": "flow_input.message" },
      "questions": {
        "type": "static",
        "value": {
          "intent": {
            "type": "choice",
            "instructions": "What does the customer want?",
            "criteria": { "refund": "Money back", "bug": "Something is broken", "other": "Anything else" }
          },
          "urgency": {
            "type": "score",
            "instructions": "How urgent is the ticket?",
            "criteria": ["Can wait", "This week", "Today", "Right now"]
          },
          "angry": { "type": "noul", "instructions": "Is the customer angry?" }
        }
      }
    }
  }
}
  • provider.kind is typesafe (model jev-latest unless a version is pinned) or cloudflare (model clef, or clef-flash for faster answers); the resource is of that same type
  • state is the content to evaluate: usually a text, such as the message to classify. To combine several values, pass an object with descriptive keys holding only what the questions need (({ message: flow_input.message, plan: results.get_account.plan })); an array of strings also works
  • questions maps each question name to { type, instructions, criteria }:
    • choice: criteria maps each option to its description (up to 255 options). The answer has choice, probabilities and confidence
    • score: criteria is an ordered array of 2 to 10 level descriptions. The answer has score, legend, probabilities and confidence
    • noul: yes/no, criteria optionally { "true": ..., "false": ... } descriptions. The answer has noul, the probability of yes from 0 to 1
  • The result is { output, model, usage } with output keyed by question name, so a later step reads results.triage.output.intent.choice, results.triage.output.urgency.score or results.triage.output.angry.noul > 0.7

Branching on the Answers

To route on the answers, put a branchone right after the decision, one branch per option, with each expr reading the decision by id:

{
  "id": "route",
  "value": {
    "type": "branchone",
    "branches": [
      { "summary": "refund", "expr": "results.triage.output.intent.choice === 'refund'", "modules": [...] },
      { "summary": "bug", "expr": "results.triage.output.intent.choice === 'bug'", "modules": [...] }
    ],
    "default": [...]
  }
}

For a yes/no question, one branch with "expr": "results.triage.output.angry.noul >= 0.5" (tune the threshold as needed) and the default as the "no" path.

As an Agent Tool

An aidecision can be a flowmodule tool of an aiagent ("tool_type": "flowmodule", "type": "aidecision"): set state to { "type": "ai" } so the calling model supplies it, and only output goes back to the model. The Tool Naming Rules apply to its summary. Only a flow's own agent step can call one, not an agent used as a tool.

Common Mistakes to Avoid

  • Missing input_transforms - Rawscript parameters won't receive values without them
  • Referencing future steps - results.step_id only works for steps that execute before the current one
  • Duplicate module IDs - Each module ID must be unique in the flow
  • AI agent flowmodule tool names with spaces - summary is the tool name and only accepts letters, numbers and underscores

Data Flow Between Steps

  • flow_input.property - Access flow input parameters
  • results.step_id - Access output from a previous step only when that step result is in scope
  • results.step_id.property - Access specific property from a previous step output only when that step result is in scope
  • flow_input.iter.value - Current iteration value inside a forloopflow; in a whileloopflow it is just the iteration index (a plain number, same as flow_input.iter.index)
  • flow_input.iter.index - Current loop index when inside a loop (forloopflow or whileloopflow)

Loop Structure Rules

  • A forloopflow runs its modules once per element of iterator, a javascript expression returning an array (e.g. results.get_items); parallel: true runs the iterations concurrently, and skip_failures: true carries on past a failed iteration
  • For whileloopflow, break the loop with a module-level stop_after_if: on the loop module itself, or on an inner step (required when that step carries state via its own results — see below)
  • stop_after_if is always a sibling of id and value on a flow module — never a direct key of the loop's value object
  • stop_after_all_iters_if is for checks after the whole loop finishes, not the normal per-iteration break condition
  • stop_after_if is evaluated after each iteration: on the loop module, result is that iteration's result (what its last step returned); on an inner step, it is that step's result
  • flow_input.iter.value in a whileloopflow is just the iteration index (same number as flow_input.iter.index) — it never carries state, so flow_input.iter.value.<field> is always undefined and a loop whose stop condition depends on it never terminates
  • To carry state across iterations, a step reads its own previous-iteration result via results.<its_own_id> with a first-iteration fallback (e.g. results.b ?? flow_input.start) — but then the loop's stop_after_if MUST sit on that inner step, not on the loop module: a body that is exactly one plain step with the stop condition on the loop module runs on a fast path where results.<step_id> is null on every iteration and the loop never terminates (bodies with 2+ steps, or whose single step has its own stop_after_if, retry or similar, resolve results across iterations regardless of stop placement)
  • For state that is just a counter, derive it from the index instead (e.g. flow_input.iter.index + 1) — that works in every configuration, including with stop_after_if on the loop module
  • If the user asks for a final scalar/object after a loop, add a normal step after the loop that extracts the final value from the loop result instead of returning the whole loop result array

Correct whileloopflow shape:

- id: loop_until_done
  stop_after_if:
    expr: result.done === true
    skip_if_stopped: false
  value:
    type: whileloopflow
    skip_failures: false
    modules:
      - id: advance_state
        value:
          type: rawscript
          input_transforms:
            count:
              type: javascript
              expr: flow_input.iter.index + 1
- id: return_final_state
  value:
    type: rawscript
    input_transforms:
      final_state:
        type: javascript
        expr: results.loop_until_done[results.loop_until_done.length - 1]

Correct whileloopflow shape carrying state via results (stop condition on the inner step):

- id: loop_until_done
  value:
    type: whileloopflow
    skip_failures: false
    modules:
      - id: advance_state
        stop_after_if:
          expr: result.done === true
          skip_if_stopped: false
        value:
          type: rawscript
          input_transforms:
            state:
              type: javascript
              expr: results.advance_state ?? flow_input.initial_state

Incorrect whileloopflow patterns:

- id: loop_until_done
  value:
    type: whileloopflow
    stop_after_if:
      expr: result.done === true
input_transforms:
  state:
    type: javascript
    # iter.value is a number (the iteration index); there is no previous-iteration state
    expr: flow_input.iter.value.count
input_transforms:
  final_state:
    type: javascript
    expr: results.loop_until_done

Approval / Suspend Structure

An approval step is a normal script step (type: rawscript or type: script) that is turned into an approval by adding a module-level suspend. Its script calls wmill.getResumeUrls(approver) to generate the secret resume/cancel URLs and returns them so they can be sent to the approver(s) (Slack, email, etc.) or approved from the run page.

  • suspend belongs on the flow module object itself, as a sibling of id and value
  • Never put suspend inside value
  • Do NOT use type: identity for an approval step. An identity step suspends but never produces the resume URLs, so approvers have no link to act on — it is not a functional approval.

Correct shape:

- id: request_approval
  suspend:
    required_events: 1
    resume_form:
      schema:
        type: object
        properties:
          comment:
            type: string
        required: [comment]
  value:
    type: rawscript
    language: bun
    input_transforms:
      approver:
        type: static
        value: ''
    content: |
      import * as wmill from "windmill-client"

      export async function main(approver?: string) {
        const urls = await wmill.getResumeUrls(approver)
        // send urls.resume / urls.cancel to the approver(s), e.g. via Slack or email
        return urls
      }

Incorrect shape (suspend misplaced inside value):

- id: request_approval
  value:
    type: rawscript
    suspend:
      required_events: 1

Incorrect shape (identity has no resume URLs — not a real approval):

- id: request_approval
  suspend:
    required_events: 1
  value:
    type: identity

Branch Result Scope Rules

  • A branchone runs the first of its branches whose expr is true, in order, and its default modules when none is; a branchall runs every branch (concurrently with parallel: true)
  • Inside a branch, you may reference earlier outer steps and earlier steps in the same branch
  • Outside a branchone, do NOT reference ids of steps that only exist inside its branches or default branch. Use results.<branchone_module_id> instead
  • Outside a branchall, do NOT reference ids of steps inside its branches. Use results.<branchall_module_id> instead
  • If downstream steps need a stable shape after a branch, make each branch return the same fields
  • When needed, add a normalization step immediately after the branch and consume results.<branch_module_id> there

Correct after branchone:

- id: route_order
  value:
    type: branchone
    ...
- id: send_confirmation
  value:
    input_transforms:
      routed:
        type: javascript
        expr: results.route_order

Incorrect after branchone:

expr: results.create_shipment
expr: results.create_backorder

Correct after branchall:

- id: enrich_parallel
  value:
    type: branchall
    parallel: true
    ...
- id: combine_data
  value:
    input_transforms:
      enrichments:
        type: javascript
        expr: results.enrich_parallel

Input Transforms

Every rawscript module needs input_transforms to map function parameters to values:

Static transform (fixed value): {"param_name": {"type": "static", "value": "fixed_string"}}

JavaScript transform (dynamic expression): {"param_name": {"type": "javascript", "expr": "results.previous_step.data"}}

Resource References

  • For flow inputs: Use type "object" with format "resource-{type}" (e.g., "resource-postgresql")
  • For step inputs: Use static value "$res:path/to/resource"

Reusing Existing Scripts and Flows

Unless the user asked for new code, look for a workspace script or flow that already does a step's job before writing it, and reuse it by path instead of copying its logic into a rawscript:

  • a workspace script: type: script with path (e.g. f/folder/send_email)
  • a workspace flow, run as a subflow: type: flow with path
  • a Hub script: type: script with a hub/<version>/<app>/<name> path

The step's input_transforms must cover the reused item's inputs, so read its input schema first.

Additional Prompt for AI

A flow's input schema may carry a top-level prompt_for_ai string, as a script's can: its author's instructions to an AI choosing the inputs. Follow it when you pick arguments to run that flow, and keep it when you rewrite the schema.

Organizing Flows: Groups and Notes

Groups and notes shape how a flow reads in the editor; neither changes what it does.

Segment every non-trivial flow into groups without waiting to be asked. Whenever a flow has more than a couple of steps, or consecutive steps form a stage ("fetch", "transform", "notify"), put them in a group, and aim for every meaningful step to belong to one. Use notes sparingly, for flow-wide information that belongs to no span of steps: the flow's purpose, key assumptions, warnings, TODOs. One note is usually enough; never label a run of steps with a note, which is what a group is for.

value.groups lists the groups, each spanning the steps from start_id to end_id:

  • start_id, end_id (required): ids of the group's first and last step; the same id for both makes a one-step group
  • summary: the group's title
  • note: markdown shown under the title
  • color: one of yellow, blue, green, purple, pink, orange, red, cyan, lime, gray, never a hex code or CSS color; leave it out and the editor picks one
  • autocollapse: true shows the group collapsed by default

The editor refuses to draw a flow whose groups break any of these rules:

  • start_id and end_id are steps of the same list: both top-level, or both in the same loop body or branch. A group can hold a loop or branch step whole, but cannot start outside one and end inside it
  • start_id does not come after end_id in that list
  • groups nest (one entirely inside another) but never partly overlap, and no two groups share both start_id and end_id
  • groups hold ordinary steps only: never preprocessor, failure, Input, Result, Trigger, or an AI agent's tools

value.notes lists sticky notes, each with a unique id, markdown text, a color from the same list, and type: free. The group note type is deprecated; use value.groups instead. Leave a note's position and size out and they are filled in for you.

Final Structural Self-Check

Before finalizing a flow, verify:

  • any preprocessor is in value.preprocessor_module
  • any failure handler is in value.failure_module
  • any approval step has module-level suspend
  • no downstream step references inner branch step ids from outside the branch
  • every AI agent flowmodule tool has a unique summary made only of letters, numbers and underscores
  • every group starts and ends on steps of the same list, start before end, nesting without partial overlap

S3 Object Operations

Windmill provides built-in support for S3-compatible storage operations.

To accept an S3 object as flow input:

{
  "type": "object",
  "properties": {
    "file": {
      "type": "object",
      "format": "resource-s3_object",
      "description": "File to process"
    }
  }
}

Using Resources in Flows

On Windmill, credentials and configuration are stored in resources. Resource types define the format of the resource.

As Flow Input

In the flow schema, set the property type to "object" with format "resource-{type}":

{
  "type": "object",
  "properties": {
    "database": {
      "type": "object",
      "format": "resource-postgresql",
      "description": "Database connection"
    }
  }
}

As Step Input (Static Reference)

Reference a specific resource using $res: prefix:

{
  "database": {
    "type": "static",
    "value": "$res:f/folder/my_database"
  }
}

OpenFlow Schema

{"OpenFlow":{"type":"object","description":"Top-level flow definition containing metadata, configuration, and the flow structure","properties":{"summary":{"type":"string","description":"Short description of what this flow does"},"description":{"type":"string","description":"Detailed documentation for this flow"},"value":{"$ref":"#/components/schemas/FlowValue"},"schema":{"type":"object","description":"JSON Schema for flow inputs. Use this to define input parameters, their types, defaults, and validation. For resource inputs, set type to 'object' and format to 'resource-' (e.g., 'resource-stripe')"},"on_behalf_of_email":{"type":"string","description":"Address of the account the flow runs on behalf of. Derived from on_behalf_of on read; accepted on write, where it is resolved to the account it names."},"on_behalf_of":{"type":"string","description":"The flow runs with the permissions of this identity: u/{username}, g/{group}, or a bare email when the username is itself email-shaped. The only stored half of the identity; on_behalf_of_email is derived from it. Omit it when writing and it is resolved from that address instead."}},"required":["summary","value"]},"FlowValue":{"type":"object","description":"The flow structure containing modules and optional preprocessor/failure handlers","properties":{"modules":{"type":"array","description":"Array of steps that execute in sequence. Each step can be a script, subflow, loop, or branch","items":{"$ref":"#/components/schemas/FlowModule"}},"failure_module":{"description":"Special module that executes when the flow fails. Receives error object with message, name, stack, and step_id. Must have id 'failure'. Only supports script/rawscript types","$ref":"#/components/schemas/FlowModule"},"preprocessor_module":{"description":"Special module that runs before the first step on external triggers. Must have id 'preprocessor'. Only supports script/rawscript types. Cannot reference other step results","$ref":"#/components/schemas/FlowModule"},"same_worker":{"type":"boolean","description":"If true, all steps run on the same worker for better performance"},"preserve_step_tags":{"type":"boolean","description":"If true and the flow runs on a custom worker tag, steps that declare their own non-empty tag run on it instead of inheriting the flow tag. Steps without their own tag still inherit the flow tag."},"concurrent_limit":{"type":"number","description":"Maximum number of concurrent executions of this flow"},"concurrency_key":{"type":"string","description":"Expression to group concurrent executions (e.g., by user ID)"},"concurrency_time_window_s":{"type":"number","description":"Time window in seconds for concurrent_limit"},"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce flow executions"},"debounce_key":{"type":"string","description":"Expression to group debounced executions"},"debounce_args_to_accumulate":{"type":"array","description":"Arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds that a job can be debounced"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of times a job can be debounced"},"skip_expr":{"type":"string","description":"JavaScript expression to conditionally skip the entire flow"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for flow results"},"cache_ignore_s3_path":{"type":"boolean"},"delete_after_secs":{"type":"integer","description":"If set, delete the flow job's args, result and logs after this many seconds following job completion"},"flow_env":{"type":"object","description":"Environment variables available to all steps. Values can be strings, JSON values, or special references: '$var:path' (workspace variable) or '$res:path' (resource).","additionalProperties":{}},"priority":{"type":"number","description":"Execution priority (higher numbers run first)"},"early_return":{"type":"string","description":"JavaScript expression to return early from the flow"},"chat_input_enabled":{"type":"boolean","description":"Whether this flow accepts chat-style input"},"notes":{"type":"array","description":"Sticky notes attached to the flow","items":{"$ref":"#/components/schemas/FlowNote"}},"groups":{"type":"array","description":"Semantic groups of modules for organizational purposes","items":{"$ref":"#/components/schemas/FlowGroup"}}},"required":["modules"]},"Retry":{"type":"object","description":"Retry configuration for failed module executions","properties":{"constant":{"type":"object","description":"Retry with constant delay between attempts","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"seconds":{"type":"integer","description":"Seconds to wait between retries"}}},"exponential":{"type":"object","description":"Retry with exponential backoff (delay doubles each time)","properties":{"attempts":{"type":"integer","description":"Number of retry attempts"},"multiplier":{"type":"integer","description":"Multiplier for exponential backoff"},"seconds":{"type":"integer","minimum":1,"description":"Initial delay in seconds"},"random_factor":{"type":"integer","minimum":0,"maximum":100,"description":"Random jitter percentage (0-100) to avoid thundering herd"}}},"retry_if":{"$ref":"#/components/schemas/RetryIf"}}},"FlowNote":{"type":"object","description":"A sticky note attached to a flow for documentation and annotation","properties":{"id":{"type":"string","description":"Unique identifier for the note"},"text":{"type":"string","description":"Content of the note"},"position":{"type":"object","description":"Position of the note in the flow editor","properties":{"x":{"type":"number","description":"X coordinate"},"y":{"type":"number","description":"Y coordinate"}},"required":["x","y"]},"size":{"type":"object","description":"Size of the note in the flow editor","properties":{"width":{"type":"number","description":"Width in pixels"},"height":{"type":"number","description":"Height in pixels"}},"required":["width","height"]},"color":{"type":"string","description":"Color of the note, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Any other value renders unstyled."},"type":{"type":"string","enum":["free","group"],"description":"Type of note - 'free' for standalone notes. 'group' notes are deprecated; segment a flow with FlowValue.groups instead."},"locked":{"type":"boolean","default":false,"description":"Whether the note is locked and cannot be edited or moved"},"contained_node_ids":{"type":"array","items":{"type":"string"},"description":"For group notes, the IDs of nodes contained within this group"}},"required":["id","text","color","type"]},"FlowGroup":{"type":"object","description":"A semantic group of flow modules for organizational purposes. Does not affect execution \u2014 modules remain in their original position in the flow. Groups provide naming and collapsibility in the editor. Members are computed dynamically from all nodes on paths between start_id and end_id.","properties":{"summary":{"type":"string","description":"Display name for this group"},"note":{"type":"string","description":"Markdown note shown below the group header"},"autocollapse":{"type":"boolean","default":false,"description":"If true, this group is collapsed by default in the flow editor. UI hint only."},"start_id":{"type":"string","description":"ID of the first flow module in this group (topological entry point)"},"end_id":{"type":"string","description":"ID of the last flow module in this group (topological exit point)"},"color":{"type":"string","description":"Color for the group in the flow editor, one of: yellow, blue, green, purple, pink, orange, red, cyan, lime, gray. Omit it to let the editor pick one."}},"required":["start_id","end_id"]},"RetryIf":{"type":"object","description":"Conditional retry based on error or result","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to retry. Has access to 'result' and 'error' variables"}},"required":["expr"]},"StopAfterIf":{"type":"object","description":"Early termination condition for a module","properties":{"skip_if_stopped":{"type":"boolean","description":"If true, following steps are skipped when this condition triggers"},"expr":{"type":"string","description":"JavaScript expression evaluated after the module runs. Can use 'result' (step's result) or 'flow_input'. Return true to stop"},"error_message":{"type":"string","nullable":true,"description":"Custom error message when stopping with an error. Mutually exclusive with skip_if_stopped. If set to a non-empty string, the flow stops with this error. If empty string, a default error message is used. If null or omitted, no error is raised."},"error_include_result":{"type":"boolean","description":"When stopping with an error (error_message set), embed the stopping step's own result inside the raised error object (as error.result) instead of discarding it. The top-level result stays { error }. Defaults to false."}},"required":["expr"]},"FlowModule":{"type":"object","description":"A single step in a flow. Can be a script, subflow, loop, or branch","properties":{"id":{"type":"string","description":"Unique identifier for this step. Used to reference results via 'results.step_id'. Must be a valid identifier (alphanumeric, underscore, hyphen)"},"value":{"$ref":"#/components/schemas/FlowModuleValue"},"stop_after_if":{"description":"Early termination condition evaluated after this step completes","$ref":"#/components/schemas/StopAfterIf"},"stop_after_all_iters_if":{"description":"For loops only - early termination condition evaluated after all iterations complete","$ref":"#/components/schemas/StopAfterIf"},"skip_if":{"type":"object","description":"Conditionally skip this step based on previous results or flow inputs","properties":{"expr":{"type":"string","description":"JavaScript expression that returns true to skip. Can use 'flow_input' or 'results.<step_id>'"}},"required":["expr"]},"sleep":{"description":"Delay before executing this step (in seconds or as expression)","$ref":"#/components/schemas/InputTransform"},"cache_ttl":{"type":"number","description":"Cache duration in seconds for this step's results"},"cache_ignore_s3_path":{"type":"boolean"},"timeout":{"description":"Maximum execution time in seconds (static value or expression)","$ref":"#/components/schemas/InputTransform"},"delete_after_secs":{"type":"integer","description":"If set, delete the step's args, result and logs after this many seconds following job completion"},"summary":{"type":"string","description":"Short description of what this step does"},"mock":{"type":"object","description":"Mock configuration for testing without executing the actual step","properties":{"enabled":{"type":"boolean","description":"If true, return mock value instead of executing"},"return_value":{"description":"Value to return when mocked"}}},"suspend":{"type":"object","description":"Configuration for approval/resume steps that wait for user input","properties":{"required_events":{"type":"integer","description":"Number of approvals required before continuing"},"timeout":{"type":"integer","description":"Timeout in seconds before auto-continuing or canceling"},"resume_form":{"type":"object","description":"Form schema for collecting input when resuming","properties":{"schema":{"type":"object","description":"JSON Schema for the resume form"}}},"user_auth_required":{"type":"boolean","description":"If true, only authenticated users can approve"},"user_groups_required":{"description":"Expression or list of groups that can approve","$ref":"#/components/schemas/InputTransform"},"self_approval_disabled":{"type":"boolean","description":"If true, the user who started the flow cannot approve"},"hide_cancel":{"type":"boolean","description":"If true, hide the cancel button on the approval form"},"continue_on_disapprove_timeout":{"type":"boolean","description":"If true, continue flow on timeout instead of canceling"},"skin":{"type":"string","enum":["detailed","minimal"],"description":"How the approval request is presented, on the approval page and in Slack/Teams approval messages. 'detailed' (used when unset) shows the flow details (arguments, graph, approvers); 'minimal' shows only the request: the step description, form and approve/reject actions"}}},"priority":{"type":"number","description":"Execution priority for this step (higher numbers run first)"},"continue_on_error":{"type":"boolean","description":"If true, flow continues even if this step fails"},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this step's jobs is restricted to (domain:action[:resource], e.g. oidc:write), on top of the flow's own restriction: a step can only narrow it. Applies to everything the step runs (loop and branch bodies, AI agent tools)."},"retry":{"description":"Retry configuration if this step fails","$ref":"#/components/schemas/Retry"},"debouncing":{"description":"Debounce configuration for this step (EE only)","type":"object","properties":{"debounce_delay_s":{"type":"integer","description":"Delay in seconds to debounce this step's executions across flow runs"},"debounce_key":{"type":"string","description":"Expression to group debounced executions. Supports $workspace and $args[name]. Default: $workspace/flow/<flow_path>-<step_id>"},"debounce_args_to_accumulate":{"type":"array","description":"Array-type arguments to accumulate across debounced executions","items":{"type":"string"}},"max_total_debouncing_time":{"type":"integer","description":"Maximum total time in seconds before forced execution"},"max_total_debounces_amount":{"type":"integer","description":"Maximum number of debounces before forced execution"}}}},"required":["value","id"]},"InputTransform":{"description":"Maps input parameters for a step. Can be a static value or a JavaScript expression that references previous results or flow inputs","oneOf":[{"$ref":"#/components/schemas/StaticTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"StaticTransform":{"type":"object","description":"Static value passed directly to the step. Use for hardcoded values or resource references like '$res:path/to/resource'","properties":{"value":{"description":"The static value. For resources, use format '$res:path/to/resource'"},"type":{"type":"string","enum":["static"]}},"required":["type"]},"JavascriptTransform":{"type":"object","description":"JavaScript expression evaluated at runtime. Can reference previous step results via 'results.step_id' or flow inputs via 'flow_input.property'. Inside for loops, use 'flow_input.iter.value' for the current iteration value (in while loops it equals 'flow_input.iter.index')","properties":{"expr":{"type":"string","description":"JavaScript expression returning the value. Available variables - results (object with all previous step results), flow_input (flow inputs), flow_input.iter (in loops)"},"type":{"type":"string","enum":["javascript"]}},"required":["expr","type"]},"AiTransform":{"type":"object","description":"Value resolved by the AI runtime for this input. The AI engine decides how to satisfy the parameter.","properties":{"type":{"type":"string","enum":["ai"]}},"required":["type"]},"AIProviderKind":{"type":"string","description":"Supported AI provider types","enum":["openai","azure_openai","azure_foundry","anthropic","mistral","deepseek","googleai","groq","openrouter","togetherai","customai","aws_bedrock","typesafe","cloudflare"]},"ProviderConfig":{"type":"object","description":"Complete AI provider configuration with resource reference and model selection","properties":{"kind":{"$ref":"#/components/schemas/AIProviderKind"},"resource":{"type":"string","description":"Resource reference in format '$res:{resource_path}' pointing to provider credentials"},"model":{"type":"string","description":"Model identifier (e.g., 'gpt-4', 'claude-3-opus-20240229', 'gemini-pro')"},"reasoning_effort":{"type":"string","description":"Provider-native reasoning effort token (e.g. 'low', 'high', 'none') for models that support extended thinking. Optional; unset leaves the provider default."}},"required":["kind","resource","model"]},"StaticProviderTransform":{"type":"object","description":"Static provider configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/ProviderConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"ProviderTransform":{"description":"Provider configuration - can be static (ProviderConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticProviderTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticProviderTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"MemoryOff":{"type":"object","description":"No conversation memory/context","properties":{"kind":{"type":"string","enum":["off"]}},"required":["kind"]},"MemoryWindow":{"type":"object","description":"Keeps the most recent messages of the memory named by the run's memory id (or the step's\nmemory_id). Without a memory id the agent runs without memory.\n","properties":{"kind":{"type":"string","enum":["window"]},"context_length":{"type":"integer","description":"Number of most recent messages to load and store. 0 turns memory off."}},"required":["kind","context_length"]},"MemoryAuto":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written: the run's memory id, else the memory_id here.\nThe step's own memory_id is not read while this kind is set; switch the kind to window\nto use it. Without a context_length, or with 0, it is off and reads previous_messages.\n","properties":{"kind":{"type":"string","enum":["auto"]},"context_length":{"type":"integer","description":"Maximum number of messages to retain in context"},"memory_id":{"type":"string","description":"Identifier for persistent memory across agent invocations"}},"required":["kind"]},"MemoryCompaction":{"type":"object","description":"Keeps the whole memory named by the run's memory id (or the step's memory_id), replacing\nits older part with a summary as the conversation approaches the model's context window.\nWithout a memory id the agent runs without memory, and compaction bounds the run's own loop.\n","properties":{"kind":{"type":"string","enum":["compaction"]},"context_window":{"type":"integer","description":"Overrides the context window looked up from the model, in tokens. Only a model\nWindmill does not know needs one; those fall back to 128000.\n"}},"required":["kind"]},"MemoryMessage":{"type":"object","description":"A single message in conversation history","properties":{"role":{"type":"string","enum":["user","assistant","system"]},"content":{"type":"string"}},"required":["role","content"]},"MemoryManual":{"type":"object","deprecated":true,"description":"Deprecated, still read as it was written. Move the step to off with previous_messages instead.","properties":{"kind":{"type":"string","enum":["manual"]},"messages":{"type":"array","items":{"$ref":"#/components/schemas/MemoryMessage"}}},"required":["kind","messages"]},"MemoryConfig":{"description":"Managed memory, stored by Windmill and replayed with each request. The memory is named by a memory id, see memory_id. While it is off, a step can supply its history in previous_messages.","oneOf":[{"$ref":"#/components/schemas/MemoryOff"},{"$ref":"#/components/schemas/MemoryWindow"},{"$ref":"#/components/schemas/MemoryCompaction"},{"$ref":"#/components/schemas/MemoryAuto"},{"$ref":"#/components/schemas/MemoryManual"}],"discriminator":{"propertyName":"kind","mapping":{"off":"#/components/schemas/MemoryOff","window":"#/components/schemas/MemoryWindow","compaction":"#/components/schemas/MemoryCompaction","auto":"#/components/schemas/MemoryAuto","manual":"#/components/schemas/MemoryManual"}}},"StaticMemoryTransform":{"type":"object","description":"Static memory configuration passed directly to the AI agent","properties":{"value":{"$ref":"#/components/schemas/MemoryConfig"},"type":{"type":"string","enum":["static"]}},"required":["type","value"]},"MemoryTransform":{"description":"Memory configuration - can be static (MemoryConfig), JavaScript expression, or AI-determined","oneOf":[{"$ref":"#/components/schemas/StaticMemoryTransform"},{"$ref":"#/components/schemas/JavascriptTransform"},{"$ref":"#/components/schemas/AiTransform"}],"discriminator":{"propertyName":"type","mapping":{"static":"#/components/schemas/StaticMemoryTransform","javascript":"#/components/schemas/JavascriptTransform","ai":"#/components/schemas/AiTransform"}}},"FlowModuleValue":{"description":"The actual implementation of a flow step. Can be a script (inline or referenced), subflow, loop, branch, or special module type","oneOf":[{"$ref":"#/components/schemas/RawScript"},{"$ref":"#/components/schemas/PathScript"},{"$ref":"#/components/schemas/PathFlow"},{"$ref":"#/components/schemas/ForloopFlow"},{"$ref":"#/components/schemas/WhileloopFlow"},{"$ref":"#/components/schemas/BranchOne"},{"$ref":"#/components/schemas/BranchAll"},{"$ref":"#/components/schemas/Identity"},{"$ref":"#/components/schemas/AiAgent"},{"$ref":"#/components/schemas/AiDecision"}],"discriminator":{"propertyName":"type","mapping":{"rawscript":"#/components/schemas/RawScript","script":"#/components/schemas/PathScript","flow":"#/components/schemas/PathFlow","forloopflow":"#/components/schemas/ForloopFlow","whileloopflow":"#/components/schemas/WhileloopFlow","branchone":"#/components/schemas/BranchOne","branchall":"#/components/schemas/BranchAll","identity":"#/components/schemas/Identity","aiagent":"#/components/schemas/AiAgent","aidecision":"#/components/schemas/AiDecision"}}},"RawScript":{"type":"object","description":"Inline script with code defined directly in the flow. Use 'bun' as default language if unspecified. The script receives arguments from input_transforms","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"content":{"type":"string","description":"The script source code. Should export a 'main' function"},"language":{"type":"string","description":"Programming language for this script","enum":["deno","bun","bunnative","python3","go","bash","powershell","postgresql","mysql","bigquery","snowflake","mssql","oracledb","graphql","nativets","php","rust","ansible","csharp","nu","java","ruby","rlang","duckdb"]},"path":{"type":"string","description":"Optional path for saving this script"},"lock":{"type":"string","description":"Lock file content for dependencies"},"type":{"type":"string","enum":["rawscript"]},"tag":{"type":"string","description":"Worker group tag for execution routing"},"concurrent_limit":{"type":"number","description":"Maximum concurrent executions of this script"},"concurrency_time_window_s":{"type":"number","description":"Time window for concurrent_limit"},"custom_concurrency_key":{"type":"string","description":"Custom key for grouping concurrent executions"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"},"assets":{"type":"array","description":"External resources this script accesses (S3 objects, resources, etc.)","items":{"type":"object","required":["path","kind"],"properties":{"path":{"type":"string","description":"Path to the asset"},"kind":{"type":"string","description":"Type of asset","enum":["s3object","resource","ducklake","datatable","volume","dbt"]},"access_type":{"type":"string","nullable":true,"description":"Access level for this asset","enum":["r","w","rw"]},"alt_access_type":{"type":"string","nullable":true,"description":"Alternative access level","enum":["r","w","rw"]}}}}},"required":["type","content","language","input_transforms"]},"PathScript":{"type":"object","description":"Reference to an existing script by path. Use this when calling a previously saved script instead of writing inline code","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the script's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the script in the workspace (e.g., 'f/scripts/send_email')"},"hash":{"type":"string","description":"Optional specific version hash of the script to use"},"type":{"type":"string","enum":["script"]},"tag_override":{"type":"string","description":"Override the script's default worker group tag"},"is_trigger":{"type":"boolean","description":"If true, this script is a trigger that can start the flow"}},"required":["type","path","input_transforms"]},"PathFlow":{"type":"object","description":"Reference to an existing flow by path. Use this to call another flow as a subflow","properties":{"input_transforms":{"type":"object","description":"Map of parameter names to their values (static or JavaScript expressions). These become the subflow's input arguments","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}},"path":{"type":"string","description":"Path to the flow in the workspace (e.g., 'f/flows/process_user')"},"type":{"type":"string","enum":["flow"]}},"required":["type","path","input_transforms"]},"ForloopFlow":{"type":"object","description":"Executes nested modules in a loop over an iterator. Inside the loop, use 'flow_input.iter.value' to access the current iteration value, and 'flow_input.iter.index' for the index. Supports parallel execution for better performance on I/O-bound operations","properties":{"modules":{"type":"array","description":"Steps to execute for each iteration. These can reference the iteration value via 'flow_input.iter.value'","items":{"$ref":"#/components/schemas/FlowModule"}},"iterator":{"description":"JavaScript expression that returns an array to iterate over. Can reference 'results.step_id' or 'flow_input'","$ref":"#/components/schemas/InputTransform"},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["forloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (faster for I/O-bound operations). Use with parallelism to control concurrency"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true. Limits resource usage. Can be static number or expression","$ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","iterator","skip_failures","type"]},"WhileloopFlow":{"type":"object","description":"Executes nested modules repeatedly until stopped. The implicit iterator is the iteration counter, so 'flow_input.iter.value' equals 'flow_input.iter.index' (0, 1, 2, ...) and never carries state. To carry state across iterations, a step reads its own previous-iteration result via 'results.<its_own_id>' with a first-iteration fallback - the loop's stop_after_if must then be on that inner step (a plain single-step body with stop_after_if on the loop module does not resolve 'results' across iterations and never terminates); plain counters can instead be derived from 'flow_input.iter.index', which works in every configuration. stop_after_if is evaluated after each iteration - on the loop module 'result' is the last iteration's result","properties":{"modules":{"type":"array","description":"Steps to execute in each iteration","items":{"$ref":"#/components/schemas/FlowModule"}},"skip_failures":{"type":"boolean","description":"If true, iteration failures don't stop the loop. Failed iterations return null"},"type":{"type":"string","enum":["whileloopflow"]},"parallel":{"type":"boolean","description":"If true, iterations run concurrently (use with caution in while loops)"},"parallelism":{"description":"Maximum number of concurrent iterations when parallel=true","ref":"#/components/schemas/InputTransform"},"squash":{"type":"boolean"}},"required":["modules","skip_failures","type"]},"BranchOne":{"type":"object","description":"Conditional branching where only the first matching branch executes. Branches are evaluated in order, and the first one with a true expression runs. If no branches match, the default branch executes","properties":{"branches":{"type":"array","description":"Array of branches to evaluate in order. The first branch with expr evaluating to true executes","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch condition"},"expr":{"type":"string","description":"JavaScript expression that returns boolean. Can use 'results.step_id' or 'flow_input'. First true expr wins"},"modules":{"type":"array","description":"Steps to execute if this branch's expr is true","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules","expr"]}},"default":{"type":"array","description":"Steps to execute if no branch expressions match","items":{"$ref":"#/components/schemas/FlowModule"}},"type":{"type":"string","enum":["branchone"]}},"required":["branches","default","type"]},"BranchAll":{"type":"object","description":"Parallel branching where all branches execute simultaneously. Unlike BranchOne, all branches run regardless of conditions. Useful for executing independent tasks concurrently","properties":{"branches":{"type":"array","description":"Array of branches that all execute (either in parallel or sequentially)","items":{"type":"object","properties":{"summary":{"type":"string","description":"Short description of this branch's purpose"},"skip_failure":{"type":"boolean","description":"If true, failure in this branch doesn't fail the entire flow"},"modules":{"type":"array","description":"Steps to execute in this branch","items":{"$ref":"#/components/schemas/FlowModule"}}},"required":["modules"]}},"type":{"type":"string","enum":["branchall"]},"parallel":{"type":"boolean","description":"If true, all branches execute concurrently. If false, they execute sequentially"}},"required":["branches","type"]},"AgentTool":{"type":"object","description":"A tool available to an AI agent. Can be a flow module or an external MCP (Model Context Protocol) tool","properties":{"id":{"type":"string","description":"Unique identifier for this tool. Cannot contain spaces - use underscores instead (e.g., 'get_user_data' not 'get user data')"},"summary":{"type":"string","description":"The name the AI agent calls this tool by, not a human label. On a flowmodule tool it must match ^[a-zA-Z0-9_]+ - letters, numbers and underscores only (e.g. 'search_documentation', not 'Search documentation') - and always be set; on an mcp or websearch tool it is a plain label. Put the human-readable explanation in 'description'."},"description":{"type":"string","description":"Free-text description of the tool given to the AI to decide when and how to call it. Overrides the description auto-derived from the underlying script."},"job_token_scopes":{"type":"array","nullable":true,"items":{"type":"string"},"description":"Scopes the token of this tool's jobs is restricted to, on top of the agent step's own restriction: a tool can only narrow it."},"value":{"$ref":"#/components/schemas/ToolValue"}},"required":["id","value"]},"ToolValue":{"description":"The implementation of a tool. Can be a flow module (script/flow) or an MCP tool reference","oneOf":[{"$ref":"#/components/schemas/FlowModuleTool"},{"$ref":"#/components/schemas/McpToolValue"},{"$ref":"#/components/schemas/WebsearchToolValue"}],"discriminator":{"propertyName":"tool_type","mapping":{"flowmodule":"#/components/schemas/FlowModuleTool","mcp":"#/components/schemas/McpToolValue","websearch":"#/components/schemas/WebsearchToolValue"}}},"FlowModuleTool":{"description":"A tool implemented as a flow module (script, flow, etc.). The AI can call this like any other flow module","allOf":[{"type":"object","properties":{"tool_type":{"type":"string","enum":["flowmodule"]}},"required":["tool_type"]},{"$ref":"#/components/schemas/FlowModuleValue"}]},"WebsearchToolValue":{"type":"object","description":"A tool implemented as a websearch tool. The AI can call this like any other websearch tool","properties":{"tool_type":{"type":"string","enum":["websearch"]}},"required":["tool_type"]},"McpToolValue":{"type":"object","description":"Reference to an external MCP (Model Context Protocol) tool. The AI can call tools from MCP servers","properties":{"tool_type":{"type":"string","enum":["mcp"]},"resource_path":{"type":"string","description":"Path to the MCP resource/server configuration"},"include_tools":{"type":"array","description":"Whitelist of specific tools to include from this MCP server","items":{"type":"string"}},"exclude_tools":{"type":"array","description":"Blacklist of tools to exclude from this MCP server","items":{"type":"string"}}},"required":["tool_type","resource_path"]},"AiAgent":{"type":"object","description":"AI agent step that can use tools to accomplish tasks. The agent receives inputs and can call any of its configured tools to complete the task","properties":{"input_transforms":{"type":"object","description":"Input parameters for the AI agent mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"output_type":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Output format type.\nValid values: 'text' (default) - plain text response, 'image' - image generation\n"},"user_message":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"The user's prompt/message to the AI agent. Supports variable interpolation with\nflow.input syntax. Required unless memory is off and previous_messages supplies\nthe prompt; image output always needs it.\n"},"system_prompt":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"System instructions that guide the AI's behavior, persona, and response style. Optional."},"streaming":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Boolean. If true, stream the AI response incrementally.\nStreaming events include: token_delta, reasoning_token_delta, tool_call, tool_call_arguments, tool_execution, tool_result\n"},"memory":{"$ref":"#/components/schemas/MemoryTransform"},"memory_id":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"String. Names the memory this step reads and writes, overriding the memory id the run\nwas started with (the chat conversation, an app chat session or the memory_id run\nparameter). Leave unset to use the run's memory id. A fixed value shares one memory\nacross every run; an expression such as flow_input.customer_id keeps one memory per\nkey. When it evaluates to an empty value the agent runs without memory. Read only\nwhile memory is window or compaction: it is ignored when memory is off, and an\nolder auto or manual memory reads neither history input.\n"},"previous_messages":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of MemoryMessage. History supplied by the flow, sent between the system prompt\nand the user message. Read only while memory is off or absent: managed memory\nignores it, and an older auto or manual memory reads neither history input.\n"},"output_schema":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"JSON Schema object defining structured output format. Used when you need the AI to return data in a specific shape.\nSupports standard JSON Schema properties: type, properties, required, items, enum, pattern, minLength, maxLength, minimum, maximum, etc.\nExample: { type: 'object', properties: { name: { type: 'string' }, age: { type: 'integer' } }, required: ['name'] }\n"},"user_attachments":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of file references (images or PDFs) for the AI agent.\nFormat: Array<{ bucket: string, key: string }> - S3 object references\nExample: [{ bucket: 'my-bucket', key: 'documents/report.pdf' }]\n"},"enabled_tools":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Array of strings naming which of the tools configured in tools the agent may call\nthis run. Leaving it unset carries every one of them; an empty array carries none.\nA tool is named as the model is shown it. An entry the model is shown nothing of is\nnamed by what identifies it instead: an MCP server by its resource path, carrying\nevery tool it exposes (which of them stays that entry's include_tools/exclude_tools),\nand a websearch entry by the reserved name '__wm_web_search', whatever summary it carries\n(no tool may take that name).\nExample: ['get_user', 'u/admin/github_mcp', '__wm_web_search']\n"},"max_completion_tokens":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Integer. Maximum number of tokens the AI will generate in its response.\nRange: 1 to 4,294,967,295. Typical values: 256-4096 for most use cases.\n"},"temperature":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Float. Controls randomness/creativity of responses.\nRange: 0.0 to 2.0 (provider-dependent)\n- 0.0 = deterministic, focused responses\n- 0.7 = balanced (common default)\n- 1.0+ = more creative/random\n"},"max_iterations":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Number. Limits how many times the agent can loop through reasoning and tool use.\nRange: 1-1000.\n"}}},"tools":{"type":"array","description":"Array of tools the agent can use. The agent decides which tools to call based on the task","items":{"$ref":"#/components/schemas/AgentTool"}},"type":{"type":"string","enum":["aiagent"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the AI agent step runs on the flow's tag (default flow)"},"omit_output_from_conversation":{"type":"boolean","default":false,"description":"If true, this AI agent step does not persist its assistant or tool messages to the flow conversation when chat mode is enabled."},"agent":{"type":"string","description":"Path of a reusable ai_agent resource (hybrid linking). When set, the agent brain\nconfig (provider/model/system prompt/etc.) and tool set are resolved at runtime from\nthat resource; the module's input_transforms then only carry the flow-local inputs\n(user_message, user_attachments, enabled_tools and the history inputs memory_id and previous_messages).\n"},"tool_inputs":{"type":"object","description":"Host-local wiring for an agent's tool inputs, keyed by tool id then input key. Binds the\nreferenced agent's tools to this flow's context (flow_input/results) without mutating the\nshared resource; overlaid onto the tools' input_transforms at runtime \u2014 including when\nagent is unset, since a step forked for editing keeps these overrides until it is saved\nback or unlinked.\n","additionalProperties":{"type":"object","additionalProperties":{"$ref":"#/components/schemas/InputTransform"}}},"parallel":{"type":"boolean","description":"If true, the agent can execute multiple tool calls in parallel"}},"required":["type","input_transforms"]},"AiDecision":{"type":"object","description":"AI decision step: one call to a decision model (TypeSafe's Jev, or Cloudflare's\nJev-compatible Clef) that answers typed questions about a state with calibrated\nprobabilities, instead of generating text.\nPrefer it over an AI agent to classify, route, score or check something: it is fast,\ncheap and its answers are structured. Its result is { output: { : answer },\nmodel, usage }, so a later step reads e.g. results..output.intent.choice. To route on\nthe answers, follow it with a branchone whose branch exprs read\nresults..output..choice. Usable as an AI agent tool, where the calling agent\nsupplies the state.\n","properties":{"input_transforms":{"type":"object","description":"Input parameters for the decision mapped to their values","properties":{"provider":{"$ref":"#/components/schemas/ProviderTransform"},"state":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"What the questions are asked about: a string, an object or an array of strings.\nAn object with descriptive keys holding only what the questions need works best.\nExample: { message: flow_input.message, plan: results.a.plan }\n"},"questions":{"allOf":[{"$ref":"#/components/schemas/InputTransform"}],"description":"Object mapping each question name to { type, instructions, criteria }, where type is:\n- 'choice': criteria maps each option to its description (up to 255); the answer\n has choice, probabilities and confidence\n- 'score': criteria is an ordered array of 2 to 10 level descriptions; the answer\n has score, legend, probabilities and confidence\n- 'noul': yes/no, criteria optionally { true, false } descriptions; the answer has\n noul, the probability of yes (0 to 1)\nExample: { intent: { type: 'choice', instructions: 'What does the customer want?',\ncriteria: { refund: 'Money back', bug: 'Something is broken' } } }\n"}},"required":["provider","state","questions"]},"type":{"type":"string","enum":["aidecision"]},"tag":{"type":"string","description":"Worker group tag for execution routing. If not set, the step runs on the flow's tag (default flow)"}},"required":["type","input_transforms"]},"Identity":{"type":"object","description":"Pass-through module that returns its input unchanged. Useful for flow structure or as a placeholder","properties":{"type":{"type":"string","enum":["identity"]},"flow":{"type":"boolean","description":"If true, marks this as a flow identity (special handling)"}},"required":["type"]},"FlowStatus":{"type":"object","properties":{"step":{"type":"integer"},"modules":{"type":"array","items":{"$ref":"#/components/schemas/FlowStatusModule"}},"user_states":{"additionalProperties":true},"preprocessor_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"}]},"failure_module":{"allOf":[{"$ref":"#/components/schemas/FlowStatusModule"},{"type":"object","properties":{"parent_module":{"type":"string"}}}]},"retry":{"type":"object","properties":{"fail_count":{"type":"integer"},"failed_jobs":{"type":"array","items":{"type":"string","format":"uuid"}}}}},"required":["step","modules","failure_module"]},"FlowStatusModule":{"type":"object","properties":{"type":{"type":"string","enum":["WaitingForPriorSteps","WaitingForEvents","WaitingForExecutor","InProgress","Success","Failure"]},"id":{"type":"string"},"job":{"type":"string","format":"uuid"},"count":{"type":"integer"},"progress":{"type":"integer"},"iterator":{"type":"object","properties":{"index":{"type":"integer"},"itered":{"type":"array","items":{}},"itered_len":{"type":"integer"},"args":{}}},"flow_jobs":{"type":"array","items":{"type":"string"}},"flow_jobs_success":{"type":"array","items":{"type":"boolean"}},"flow_jobs_duration":{"type":"object","properties":{"started_at":{"type":"array","items":{"type":"string"}},"duration_ms":{"type":"array","items":{"type":"integer"}}}},"branch_chosen":{"type":"object","properties":{"type":{"type":"string","enum":["branch","default"]},"branch":{"type":"integer"}},"required":["type"]},"branchall":{"type":"object","properties":{"branch":{"type":"integer"},"len":{"type":"integer"}},"required":["branch","len"]},"approvers":{"type":"array","items":{"type":"object","properties":{"resume_id":{"type":"integer"},"approver":{"type":"string"}},"required":["resume_id","approver"]}},"failed_retries":{"type":"array","items":{"type":"string","format":"uuid"}},"skipped":{"type":"boolean"},"agent_actions":{"type":"array","items":{"type":"object","oneOf":[{"type":"object","properties":{"job_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"type":{"type":"string","enum":["tool_call"]},"module_id":{"type":"string"}},"required":["job_id","function_name","type","module_id"]},{"type":"object","properties":{"call_id":{"type":"string","format":"uuid"},"function_name":{"type":"string"},"resource_path":{"type":"string"},"type":{"type":"string","enum":["mcp_tool_call"]},"arguments":{"type":"object"}},"required":["call_id","function_name","resource_path","type"]},{"type":"object","properties":{"type":{"type":"string","enum":["web_search"]}},"required":["type"]},{"type":"object","properties":{"type":{"type":"string","enum":["message"]}},"required":["content","type"]}]}},"agent_actions_success":{"type":"array","items":{"type":"boolean"}}},"required":["type"]}}