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N8n Binary And Data Official

Organization
n8n-io
n8n-binary-and-data-official

Use when handling files, images, attachments, or binary data in n8n, OR when an AI agent needs to take a user-uploaded file as tool input or return a generated file. For Data Tables (schemas, dedup, persistent state), see the separate n8n-data-tables-official skill. Triggers on "file", "image", "PDF", "attachment", "binary", "upload", "download", chat trigger with files, agent tool that needs a file, vision/multimodal, or any handling of non-JSON file data.

Overview

Publishern8n-io
Repositoryskills
Skill namen8n-binary-and-data-official
Stars
551
Forks
80
Bundled files
4
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by n8n-io on GitHub. Read the source before you install it.

Installation

Install the N8n Binary And Data Official AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/n8n-io/skills/tree/main/skills/n8n-binary-and-data-official
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/n8n-io/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/n8n-binary-and-data-official .claude/skills/n8n-binary-and-data-official
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable N8n Binary And Data Official in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads N8n Binary And Data Official on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so N8n Binary And Data Official is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

n8n Binary and Data

n8n handles two kinds of data: JSON (in $json) and binary (in $binary), flowing side-by-side. Binary has sharp edges around agent tools, storage, and display contexts (chat surfaces, message rendering).

For tabular storage (Data Tables), see the n8n-data-tables-official skill.

Non-negotiables

  1. Binary is in $binary, not $json. Don't read file contents from $json.
  2. Binary cannot cross the agent tool boundary in either direction. Tool parameters are JSON only (via fromAi()), and tool results are JSON only. Pre-stage binary in storage and pass keys/URLs through JSON. The agent's passthroughBinaryImages: true lets the LLM see uploaded images for vision, but it does NOT enable tools to receive them. See references/AGENT_TOOL_BINARY.md.

Strong defaults

  • Merge nodes keep binary in context. When a side computation strips binary, merge it back rather than re-fetching. See references/MERGE_FOR_CONTEXT.md.

Binary basics

In n8n, each item has two slots:

ts
{
    json: { ... },           // your data
    binary: {                // your files
        data: {              // 'data' is the typical key; can be any name
            data: '<base64>',
            mimeType: 'application/pdf',
            fileName: 'invoice.pdf',
            fileExtension: 'pdf',
        },
    },
}

$binary.<key> reads the named property. Most file-handling nodes have a binaryPropertyName parameter, the key inside $binary.

Setting binary

File-producing nodes (HTTP Request with binary response, Read Files, etc.) populate $binary automatically. To produce binary in a Code node:

ts
return [{
    json: { ... },
    binary: {
        data: {
            data: Buffer.from(content).toString('base64'),
            mimeType: 'text/plain',
            fileName: 'output.txt',
        },
    },
}]

Reading binary

ts
// In a Code node
const buffer = await this.helpers.getBinaryDataBuffer(0, 'data')
const text = buffer.toString('utf-8')

Most workflows don't need to read binary directly. Pass it through to consumer nodes (email attachments, file uploads, etc.).

See references/BINARY_BASICS.md for more.

Agent tool gymnastics

Agent tools (sub-workflows wired into an AI Agent node or a first-class n8n Agent, or workflows exposed as MCP tools) have a constraint: parameters and results are JSON, not binary. Affects both directions.

Inbound (user uploads → tool consumes): the chat trigger gives files[]. The agent can have passthroughBinaryImages: true for vision, but fromAi() can't pass binary to a tool. So:

  1. Pre-stage uploaded files: hash a key, upload to private storage.
  2. Inject the keys into the agent's system prompt: "Files passed in: [{originalFileName, fileName}]. Use EXACTLY the fileName field when calling tools."
  3. The tool's fromAi('imageName', '...', 'string') receives the key. The sub-workflow downloads from storage.

Outbound (tool produces → agent returns): a tool generates a file. It can't return raw binary.

  1. Generate binary internally.
  2. Upload to storage, get back URL/key.
  3. Return JSON: { ok: true, file_id: '...', url: '...' }.
  4. The agent embeds the URL in its response, or another tool fetches by key.

For the full pattern including the async-via-webhook variant for long-running tools, see references/AGENT_TOOL_BINARY.md.

Merge for keeping binary in context

A JSON-only operation (Edit Fields, Code, IF) often strips binary from the item. To keep it:

[Source with binary] ─┬─→ [Edit Fields: transform JSON] ─┐
                      │                                    ├─→ [Merge: by position] ─→ [Email with attachment]
                      └─────────────────────────────────────┘

Merge combines the streams, and binary survives. See references/MERGE_FOR_CONTEXT.md.

CDN requirement for chat surfaces

When a workflow generates an image and the user wants it embedded in a chat message (Slack, Discord, Teams, Telegram, embedded webhook chat, etc.):

  • Binary on the item isn't enough. Chat surfaces don't read $binary; they render messages that reference images by URL (or via platform-specific file upload APIs).
  • The image must live somewhere a URL can fetch. Upload to a CDN or object store first.
  • The user configures this storage. Not built into n8n.

Common options span object storage (S3, R2, GCS, Azure Blob, Vercel Blob, Supabase Storage) and drive-style services (Dropbox, Google Drive, OneDrive, Box). Ask the user what they use rather than defaulting to S3.

See references/CDN_REQUIREMENT.md.

Data Tables

For Data Tables, see the n8n-data-tables-official skill. Distinct surface with its own gotchas (default columns, no foreign keys, no JSON column type, manual-mapping UI quirk).

Reference files

FileRead when
references/BINARY_BASICS.mdFirst time handling binary, or reading/writing the $binary slot
references/AGENT_TOOL_BINARY.mdAgent tool needs a user-uploaded file, or produces a file (the boundary in either direction)
references/MERGE_FOR_CONTEXT.mdBinary disappears after a JSON transform and needs to re-attach
references/CDN_REQUIREMENT.mdShowing images in a chat surface or other places that need URL-referenced images

Anti-patterns

Anti-patternWhat goes wrongFix
Trying to read file content from $jsonBinary isn't in $jsonUse $binary
Building an agent tool that returns binary directlyTool output is JSON-only, so binary doesn't surviveUpload to storage, return key/URL in JSON (see AGENT_TOOL_BINARY.md)
Trying to pass uploaded chat files into a tool via fromAifromAi doesn't carry binary, so the tool gets nothingPre-stage uploads to storage, inject keys in the system prompt, and have the tool download by key
Setting passthroughBinaryImages: true and assuming tools can now see the fileThe flag only affects what the LLM sees, not what tools receiveStill need the upload-and-pass-key pattern for tools
Losing binary after a JSON transformThe transform's output item doesn't have binaryUse Merge to combine the JSON output with the binary stream
Storing image in n8n binary and expecting a chat surface to displayChat surfaces need URL-accessible images (or a platform-native file upload), not raw $binaryUpload to CDN, embed URL or use the platform's file API
Hardcoding binary base64 in a Code nodeMassive workflow JSON, slow, leakyReference binary via $binary properly, or upload to storage and reference by URL

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the N8n Binary And Data Official AI skill do?

Use when handling files, images, attachments, or binary data in n8n, OR when an AI agent needs to take a user-uploaded file as tool input or return a generated file. For Data Tables (schemas, dedup, persistent state), see the separate n8n-data-tables-official skill. Triggers on "file", "image", "PDF", "attachment", "binary", "upload", "download", chat trigger with files, agent tool that needs a file, vision/multimodal, or any handling of non-JSON file data.

Why use N8n Binary And Data Official on TypingMind?

Because you install it once and use it with any model. N8n Binary And Data Official is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install N8n Binary And Data Official in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/n8n-io/skills/tree/main/skills/n8n-binary-and-data-official. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use N8n Binary And Data Official?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with N8n Binary And Data Official?

As many as you like. As long as a model supports skills, you can use N8n Binary And Data Official with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the N8n Binary And Data Official AI skill free?

Yes. It is published on GitHub by n8n-io under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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