/n8n-subworkflows

name: n8n-subworkflows
description: Build reusable, composable n8n sub-workflows. Use when extracting shared logic, building anything multi-step or reused across workflows, or any workflow over ~10 nodes — and whenever the user mentions sub-workflows, Execute Workflow, reuse, shared/common logic, modular workflows, "Define Below" inputs, waitForSubWorkflow, mode each vs all, or exposing a workflow as an agent tool. Covers typed sub-workflow inputs, all-vs-each execution, verb-first naming for discovery, stateless vs stateful design, and splitting by input shape.

n8n Sub-workflows

A sub-workflow is a reusable function. An **Execute Workflow Trigger** declares typed inputs, the body does the work, and the last node returns the output. A caller invokes it through an **Execute Workflow** node like any other step.

That framing buys you the things functions buy you everywhere: encapsulation, reuse, testability, replaceability. It's the primary reuse mechanism in n8n, and it's badly underused. Without it, the same logic gets copy-pasted across workflows — then a bug gets fixed in two places, the third copy gets missed, and your "identical" copies quietly drift apart.

This skill is about when to reach for a sub-workflow, how to define its input/output contract so callers (and agents) can actually use it, how to call it correctly (`all` vs `each`, blocking vs fire-and-forget), and how to name it so it gets found instead of rebuilt.

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The two non-negotiables

Everything else is judgement. These two are not.

1. Search before you build

Before you write logic for a generic problem, check whether a sub-workflow already does it. The community MCP can't filter workflows by tag, so the **name is the discovery surface**:

n8n_list_workflows()                          # scan the library
n8n_get_workflow({ id: "<candidate>" })       # read its inputs/outputs + body

If something fits, use it and tell the user ("I found `Subworkflow: Parse RFC2822 date` — using that"). If nothing fits, build it *with a discoverable name* so the next search finds it. The discovery convention (verb-first prefixes) lives in **NAMING_AND_DISCOVERY.md**.

2. The Execute Workflow Trigger uses "Define Below" with typed fields — not passthrough

The trigger has two input modes. **Default to "Define Below"** with explicit typed fields. Define Below is the only mode that gives callers a schema to fill — it's what lets an AI agent pass values via `$fromAI` and what lets structured callers map fields cleanly. Passthrough has no schema, so the trigger can't be wired as a clean agent tool and structured callers have nothing to bind to.

Two exceptions, and only two:

• **Binary input.** Typed fields are JSON-only. If the sub-workflow must receive an image/file/PDF, you need passthrough so the `binary` slot flows through.
• **Zero inputs.** Define Below requires at least one field. A genuinely no-arg operation ("list active credentials", "current count") has nowhere to put an empty schema, so passthrough is the only option.

Outside those two cases, passthrough is a bug. See "Inputs and outputs as a contract" below.

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Should this be a sub-workflow?

You're about to write a chunk of logic. Run it through this:

Could this plausibly be needed in another workflow?
  └─ Yes → extract.

Is it a generic concern (auth, retry, parsing, formatting, ID generation)?
  └─ Almost always → extract. These are the canonical reusable sub-workflows.

Is it >5 nodes and conceptually one thing?
  └─ Probably extract, even if reuse isn't certain. It's better isolated.

Is it one HTTP call with no logic around it?
  └─ Don't. A sub-workflow that's just trigger → HTTP → return adds a boundary
     for nothing.

Is it tightly coupled to this one caller's data shape?
  └─ Don't extract yet — fix the data shape first, or you just relocate the coupling.

The reasons to extract go beyond reuse:

• **Readability.** The caller shows one node ("Parse date") instead of five.
• **Testability.** Run the sub-workflow alone with pinned input (`n8n_test_workflow`).
• **Replaceability.** Swap the implementation without rippling to callers.

A 20-node workflow is fine *if it's mostly a linear sequence of Execute Workflow calls and decisions* — each node has one purpose, and you inspect a section by opening the sub-workflow it calls. A 20-node workflow of inline transformations is not fine. If yours has 15+ nodes and isn't mostly sub-workflow calls and branches, extract more.

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Stateless vs. stateful (deliberately)

Both are first-class. The choice is about intent and what the contract promises.

**Stateless** — input in, output out, no I/O beyond that. The default for pure logic. When you need it again, you call it without worrying about side effects firing.

• `Subworkflow: Parse RFC2822 date` — date string → ISO date or error.
• `Subworkflow: Compute MRR from subscription` — subscription object → number.
• `Subworkflow: Format invoice as HTML` — invoice data → HTML string.

**Stateful (deliberate)** — reads or writes external state *behind a clean contract*. This is the repository pattern: the sub-workflow abstracts the storage operation so callers think in domain terms, not SQL.

• `Customer: get by id` — id → customer object or `{ ok: false, error: "not_found" }`. Reads the DB.
• `Customer: write billing record` — record → `{ ok: true, id }`. Writes the DB.
• `Notify: send to on-call` — channel, message → `{ ok: true, messageId }`. Calls Slack/SMTP.

Why build these as sub-workflows: callers think `get customer by id` instead of writing the query; you can swap the store (Postgres → Supabase, native node → HTTP) without touching a single caller; and idempotency, retry, and validation get centralized in one place.

What to avoid is **accidental state** — a sub-workflow named and described as pure that quietly writes to a log table. That ambushes every caller who reasonably assumed it was safe to retry or compose. Ei