N8n Loops Official

n8nOfficialPublished by n8n

Skill
Tool integration
Automation and integrations
Apache-2.0
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From the author

Use when working with multi-item data, batches, paginated APIs, rate-limited APIs, fan-out across multiple branches, anything that needs to "do this for each", or any time the user mentions looping, iterating, batching, paging, parallelism, or "loop over items". Triggers on "loop", "iterate", "for each", "batch", "page through", "paginate", "rate limit", "process all", "fan-out", "parallel branches", "concurrency", or any node that should run once vs once-per-item.

— the description by n8n

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides the definitive guide to handling multi-item data in n8n. It clarifies the distinction between implicit per-item iteration, single-fire execution, and explicit batching. It teaches users how to leverage built-in node behaviors, the Loop Over Items node, and HTTP pagination to build efficient, scalable, and error-resistant automation pipelines.

What it does

Explains the default per-item iteration behavior of n8n nodes.
Defines when and how to use the executeOnce setting to prevent redundant processing.
Provides a decision tree for selecting the correct looping mechanism.
Details the configuration of the Loop Over Items node for batching and rate limiting.
Outlines native HTTP Request pagination for efficient API data retrieval.
Identifies common anti-patterns like unnecessary loops and double-webhook responses.

When to use it

When you need to process data in batches or chunks.
When an API requires pagination to fetch all records.
When a node should run exactly once regardless of the number of input items.
When you need to implement rate limiting or delays between processing steps.
When you need to perform stateful iteration or complex multi-branch convergence.

Advantages

Prevents common performance issues caused by redundant node executions.
Reduces API consumption by utilizing native pagination instead of manual loops.
Improves workflow readability by removing unnecessary loop nodes.
Ensures reliable data aggregation and notification handling.
Provides clear patterns for complex tasks like recursive sub-workflows.

Usage examples

“How do I make sure my Slack notification only sends once after processing 50 items?”: The agent will instruct you to enable the executeOnce setting on the Slack node, ensuring it fires once for the entire dataset rather than once per item.
“I need to process 1000 records from an API that returns 50 items per page. How do I get them all?”: The agent will guide you to use the HTTP Request node's built-in Pagination option, configuring it to automatically fetch all pages until the API returns an empty response.
“How can I send emails in batches of 10 with a delay between each batch?”: The agent will show you how to use the Loop Over Items node with a batchSize of 10, followed by a Wait node, to control the flow and rate of your email sends.
“I have a loop that is running too many times, what should I do?”: The agent will help you determine if you can delete the Loop Over Items node entirely and rely on n8n's default per-item iteration, or if you need to adjust your merge logic.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/n8n-io/n8n-loops-official/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip n8n-loops-official.zip -d .agents/skills

Documentation by n8n

n8n Loops

Three meanings of "loop" map to three mechanisms:

"Run this node for every item." Default. Most nodes loop automatically, so do nothing.
"Run this node once with all items, not once per item." The executeOnce setting (single boolean).
"Process items in explicit batches with control flow between iterations." The Loop Over Items node (formerly Split In Batches).

For paginated APIs, the HTTP Request node has built-in pagination. Almost always preferable to a hand-built page-counting loop.

The model: items are an array

Data flows between nodes as an array of items, each { json: {...}, binary?: {...} }. 50 items = 50-entry array.

Default: a node runs once per item. An HTTP Request with 50 input items fires 50 requests and outputs 50 result items. This is the implicit loop most workflows rely on.

The input array is the loop. Control iteration by controlling the array.

Non-negotiable

executeOnce: true whenever a node should fire once-per-run, not once-per-item. Includes any expression aggregating across the dataset via $input.all() / $('Node').all() plus .map() / .filter() / .reduce() (without it, the aggregate computes N times for N upstream items, often producing N duplicates downstream). Also includes single notifications, aggregate writes, summary messages.

Counter-case: .all() combined with another node's .item (a per-item lookup, e.g., $('Get Tags').all().filter(tag => $('Search Posts').item.json.tag_ids.includes(tag.json.id))) is real per-item work and should keep executeOnce off. See the n8n-expressions-official skill's executeOnce section for the full distinction.

Strong defaults

Don't build a loop when default iteration suffices. Most nodes (HTTP Request, native service nodes, Set, IF/Switch) run once per input item automatically: N items in, N runs. To make N HTTP calls or create N records, just connect the source to the node. Don't reach for Loop Over Items unless you need per-iteration control. (Note: Execute Workflow is the exception. It defaults to a single all-items batch. See n8n-subworkflows-official for mode: 'each'.)
For paginated APIs, use HTTP Request's built-in pagination. Don't reinvent with Loop Over Items + manual $pageCount unless the API is genuinely odd. See references/HTTP_PAGINATION.md.
Loop Over Items is for explicit batching or per-iteration control (rate limiting, per-batch error recovery, stateful chunks, polling). See references/LOOP_OVER_ITEMS.md.
Per-item iteration is sequential, not parallel. Each item completes before the next starts, even on parallel looking branches. For a real concurrency pattern, see n8n-subworkflows-official.

Decision tree: which mechanism do I need?

Need to do something for each item?
├── Default per-item iteration is enough
│   └── Just connect the node. Done.
│
├── The node should run once total, not once per item?
│   └── Set executeOnce: true on the node
│
├── Paginated API (multiple HTTP calls to fetch all pages)?
│   └── Use HTTP Request's Pagination option (see references/HTTP_PAGINATION.md)
│
├── Need explicit batching (rate limit, chunk size, per-batch error handling)?
│   └── Use Loop Over Items node (see references/LOOP_OVER_ITEMS.md)
│
└── Need to recurse / repeat with state until a condition is met?
    └── Loop Over Items with Reset, OR a sub-workflow that calls itself.
        Both are advanced patterns; see references/LOOP_OVER_ITEMS.md.

`executeOnce`: the single-fire setting

Every node's Settings tab has an Execute Once toggle. When on, the node runs once using only the first input item. In SDK code, set executeOnce: true as shown; on an existing workflow, apply it via update_workflow setNodeSettings (n8n 2.24.0+).

{
    name: 'Aggregate Slack',
    type: 'n8n-nodes-base.slack',
    parameters: { /* ... */ },
    executeOnce: true,
}

When to use it:

Notifications and aggregate writes. A "summary message" shouldn't fire 100 times because 100 items came in.
Counters, totals, reports. Anything computing $input.all().length etc. should run once.
Expressions aggregating across the full array via $input.all() / $('Node').all(). Otherwise the aggregate runs per upstream item. (Per-item lookups using .all() filtered by another node's .item are the counter-case, see n8n-expressions-official.)

When NOT to use it:

Per-item operations. One notification per item is the default and usually correct.
HTTP requests fanning out per item. You want one call per item.

Most common mistake: forgetting executeOnce on an aggregate node, then seeing the same message fire 50 times after a fan-out.

When the implicit loop bites you

Default per-item iteration is great until it isn't. Common surprises:

A "single" config node fires per item

A Set node after a fan-out runs once per item, producing N copies of the same constants. Usually fine, but expensive expressions (long JSON.stringify, Luxon parse) run N times. Move the Set above the fan-out, or set executeOnce: true.

An aggregate Code node runs N times

A Code node reading $input.all() to compute a sum runs once per upstream item without executeOnce: true, producing N identical items. Set executeOnce: true.

A respond-to-webhook fires twice

Most painful version. Respond-to-Webhook fires per input item, and two branches converging without a merge fire it twice: first response wins, the rest log errors. Merge first, or ensure only one branch reaches the responder. See n8n-node-configuration-official references/MERGE_NODE.md.

An LLM call fires N times when you wanted one summary

Same shape as the aggregate Code node. An LLM node with $input.all() in its prompt makes N identical calls, costs N tokens, returns N identical answers without executeOnce: true.

When to reach for `Loop Over Items`

Default iteration handles most cases. Use Loop Over Items for:

Rate limiting. "Process 10 at a time, 1s wait between batches."
Batched API calls with array bodies. "Send 50-item chunks to /bulk."
Per-batch error handling. "If a batch fails, log and continue."
Stateful iteration. "Each iteration depends on the previous output."
Polling a long-running job. "Start, check status every 30s until done or capped." Uses reset: true plus a $runIndex ceiling.
Per-item multi-branch with aggregation. "For each input, run transforms in parallel, merge, then aggregate." The done output (index 0) carries the result.

For wiring details, the output-index gotcha (output 0 = done, output 1 = loop), and worked examples, see references/LOOP_OVER_ITEMS.md.

When NOT to reach for `Loop Over Items`

The most common rationalization: "I need to wait for all items to finish before the next step, so I'll add Loop Over Items and use the done output." You don't need Loop Over Items for that. Default per-item iteration already waits: each item flows through the full downstream chain before the next item starts, and the post-loop node never fires "early."

The cure for that mistake is almost always: delete the Loop Over Items node, change nothing else, ship. That is Scenario 1 below, and it covers the majority of cases.

The four scenarios are independent. Read them as separate decisions, not as alternatives that all "replace" Loop Over Items. Most builds hit Scenario 1 and are done. Scenarios 2 and 3 only enter the picture when their specific goal applies. Scenario 4 is the narrow case where Loop Over Items actually earns its place.

Scenario 1: default per-item iteration (the default, most common)

Source emits N items, per-item processor runs N times, downstream chain follows. No Loop Over Items, no executeOnce, no Aggregate. Just connect the nodes.

[Source: 20 items]
  → [Per-item processor]   # default iter, runs 20 times
  → [Next step]            # runs after each item, in order

If a Loop Over Items + done was added here "to wait for all items" or "to make the next node run for each item," delete the Loop Over Items node and wire source straight to processor. Do not replace it with anything. Default iteration already does the job. The exception is Execute Workflow (sub-workflow): it defaults to a single all-items batch, so per-item invocation needs mode: 'each' on that node, not a Loop. See n8n-subworkflows-official.

Scenario 2: a downstream node should fire once total (`executeOnce: true`)

Independent of Scenario 1. Triggered only when there is a SPECIFIC downstream node whose job is once-per-run, not once-per-item: one digest email after 20 papers process, one summary write after the loop, one final Slack notification.

Set executeOnce: true on that node. The node receives all upstream items but runs once. This is a per-node setting, not a Loop replacement: the per-item processor in Scenario 1 still runs N times, and only this one downstream node collapses.

Scenario 3: a node needs the items as a single array (Aggregate)

Independent of Scenario 1. Triggered only when a downstream node's input contract is a list, not per-item invocations (e.g., a node taking a JSON array body, an LLM prompt that needs the whole list).

Use the Aggregate node to collapse the per-item stream into one item containing the array. Again, not a Loop replacement.

Scenario 4: genuine batching (the only time Loop Over Items earns its place)

Rate limiting (process N at a time with a Wait between batches), chunked bulk API calls (POST 50-item arrays to /bulk), per-batch error handling, polling a long-running job with reset: true and a $runIndex ceiling, stateful iteration where each batch depends on the previous output.

"Wait for items to finish" does not qualify. Default iteration already does that.

Quick disambiguation

If your only reason for the Loop is "wait for items / run for each item," you are in Scenario 1. Delete the Loop. Do not add executeOnce or Aggregate as a substitute. They solve different problems and are only added when their own scenario applies.

When to reach for HTTP pagination

Three common page shapes:

Next-URL in response. Each response includes a next link.
Page number/cursor parameter. Bump ?page=N or ?cursor=... each call.
Stop on empty page or specific status.

HTTP Request handles all natively via its Pagination option: set the mode, give a next-page expression, and the node loops internally, returning a single output array of all pages' items.

Don't reinvent with Loop Over Items + manual $pageCount unless the API does something the built-in modes can't express.

See references/HTTP_PAGINATION.md.

Sub-workflow recursion

For genuinely recursive work (tree walking, retry-with-backoff, "process this and its children"), a self-calling sub-workflow is cleaner than Loop Over Items with Reset. Input parameters carry recursion state.

Sub-workflow: Walk Tree
  inputs: { node_id, depth }
  body: process node, look up children, for each child call self with depth+1

Watch recursion depth. n8n has nested-execution limits. For deep recursion, a queue + flat loop beats true recursion.

Reference files

File	Read when
`references/LOOP_OVER_ITEMS.md`	Configuring the Loop Over Items node, batching, rate limiting, stateful iteration
`references/HTTP_PAGINATION.md`	Calling a paginated API, configuring HTTP Request pagination modes

Anti-patterns

Anti-pattern	What goes wrong	Fix
Adding `Loop Over Items` to "make it loop" when default iteration already does	Workflow harder to read for no benefit, and loop output vs done output gets miswired	Just connect the node directly and let default iteration handle it
Aggregate Code node without `executeOnce`	Same aggregate computed N times, output has N identical items	Set `executeOnce: true`
Manual pagination loop with `Loop Over Items` + `$pageCount`	Reinvents what HTTP Request does natively, with brittle stop conditions	Use HTTP Request's `Pagination` option
Sending one Slack message per item when you wanted a summary	Slack channel floods, rate limits hit, embarrassment	`executeOnce: true` on the Slack node, build the summary upstream
Two branches both reach `Respond to Webhook`	Responds twice, downstream callers see errors	Merge before the responder, or ensure only one branch reaches it
`Loop Over Items` with `Reset` and no clear termination	Infinite loop, n8n eats memory until the execution is killed	Always have a clear termination condition. Prefer HTTP pagination for paged APIs
Nesting one `Loop Over Items` inside another in the same workflow	Broken at runtime, validation passes	Move the inner loop into a sub-workflow called per outer iteration. See `n8n-subworkflows-official` `mode: 'each'`

Files

ATTRIBUTION.mdAdded by AutoGineer842 B
LICENSELicence file added by AutoGineer11.0 KiB
SKILL.md13.3 KiB
references/HTTP_PAGINATION.md9.4 KiB
references/LOOP_OVER_ITEMS.md12.0 KiB

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Node.js

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Attribution and licence

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n8n

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n8n (Official)

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n8n-io/skills · skills/n8n-loops-official · commit 27b6b9f

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LICENSE (added by AutoGineer from LICENSE)
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2026-11-08

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