# N8n Code Tool

> n8n Custom Code Tool

- Skill: `s3yed/n8n-code-tool-2` (Agent Skill)
- Install (CLI): `npx skillmds@latest add s3yed/n8n-code-tool-2`
- Raw SKILL.md: https://api.skillmd.com/api/skills/s3yed/n8n-code-tool-2/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: S3YED (https://skillmd.com/u/s3yed)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/s3yed/n8n-code-tool-2

---


# n8n Custom Code Tool

Expert guidance for writing code inside `@n8n/n8n-nodes-langchain.toolCode` — the tool an AI Agent can invoke, **not** the regular workflow Code node.

---

## ⚠️ This is NOT the Code node

The Custom Code Tool looks like a Code node in the editor — same JavaScript editor, similar layout — but it is a **completely different node** from a different package with a **different runtime contract**.

| | Code node | Custom Code Tool |
|---|---|---|
| **Node type** | `n8n-nodes-base.code` | `@n8n/n8n-nodes-langchain.toolCode` |
| **Package** | `n8n-nodes-base` | `@n8n/n8n-nodes-langchain` |
| **Invoked by** | Previous node (workflow flow) | AI Agent (LangChain) |
| **Input** | `$input.all()` — item stream | `query` — string or object from LLM |
| **Return** | `[{json: {...}}]` (items array) | **A string** |
| **`$fromAI()`** | N/A | **Not available** (see Errors) |
| **HTTP helper** | `this.helpers.httpRequest` (auth helpers blocked) | Not exposed to the tool sandbox |
| **State** | Per-run execution data | No `getContext`, no `$getWorkflowStaticData` |

**If you treat it like a Code node, it fails.** The rest of this skill covers the Code Tool's actual contract.

---

## Quick Start

### Minimal JavaScript Code Tool

```javascript
// `query` is whatever the AI sent (a string by default)
return `You asked: ${query}`;
```

### Minimal Python Code Tool

```python
# `_query` is whatever the AI sent (a string by default)
return f"You asked: {_query}"
```

### Essential Rules

1. **Return a string.** Numbers are auto-converted. Anything else throws `"The response property should be a string, but it is an object"`.
2. **Input variable is fixed**: `query` (JS), `_query` (Python). You cannot rename it.
3. **Do NOT use `$fromAI()`** inside the Code Tool sandbox — it throws `"No execution data available"`.
4. **Do NOT use `[{json: {...}}]`** return format — that's for Code nodes. Throws `"Wrong output type returned"`.
5. **Use a descriptive tool name** (letters/numbers/underscores, v1.1+). The agent calls the tool by its name.
6. **Write a precise description** — the LLM decides whether to invoke the tool based on it.

---

## The Two Input Modes

The Code Tool has two input shapes, controlled by `specifyInputSchema`:

### Mode 1: Unstructured (default, `specifyInputSchema: false`)

The AI passes **a single string** as `query`. If you need multiple fields, the AI has to stuff them into that one string and you parse them out. In practice, LLMs will happily pass a JSON string if your description tells them to.

```javascript
// Parse a JSON string the AI sent
let params;
try {
  params = typeof query === 'string' ? JSON.parse(query) : query;
} catch (e) {
  throw new Error('Expected a JSON object. Parser said: ' + e.message);
}
const price = Number(params.price);
const months = Number(params.months);
// ...
return JSON.stringify({ monthly_payment: /* ... */ });
```

**Pros**: simplest to set up, one field to describe.
**Cons**: no schema validation — if the LLM forgets a field, the tool throws at runtime.

**Best for**: quick prototypes, tools with one natural input (a question, a URL, a text blob).

### Mode 2: Structured (`specifyInputSchema: true`)

The tool becomes a LangChain `DynamicStructuredTool`. The LLM sees a typed argument schema and passes a **validated object** as `query`. You access fields directly.

```javascript
// query is now an object matching your schema
const price = query.price;
const months = query.months;
const residual_percent = query.residual_percent;

const monthly = computeAnnuity(price, months, residual_percent);
return JSON.stringify({ monthly_payment: monthly });
```

Schema is defined via either:
- `schemaType: "fromJson"` + `jsonSchemaExample` (n8n v≥1.3) — paste an example JSON, n8n infers the schema
- `schemaType: "manual"` + `inputSchema` — write a full JSON Schema yourself

**Pros**: LLM gets type hints, invalid calls rejected before your code runs, cleaner code.
**Cons**: a little more setup; requires n8n version with schema support.

**Best for**: production tools with multiple typed parameters (calculators, API wrappers, anything with numeric fields the LLM tends to stringify).

**See**: [INPUT_SCHEMA.md](INPUT_SCHEMA.md) for complete schema setup.

---

## Return Format

**The return value must be a string.** The LLM reads it as the tool's observation.

```javascript
// ✅ String
return "42";

// ✅ Number (auto-converted to string by n8n)
return 42;

// ✅ JSON-encoded structured result (recommended for rich output)
return JSON.stringify({ result: 42, currency: "SEK" });

// ❌ Raw object → "The response property should be a string, but it is an object"
return { result: 42 };

// ❌ Workflow item format → "Wrong output type returned"
return [{ json: { result: 42 } }];

// ❌ Array → "The response property should be a string, but it is an object"
return [1, 2, 3];
```

### Best practice: JSON-stringify structured results

When your tool has more than a trivial scalar output, return a JSON string:

```javascript
return JSON.stringify({
  monthly_payment_sek: 5405,
  loan_amount: 351920,
  total_cost_of_credit: 63295
});
```

The LLM parses JSON reliably and can pick the fields it needs to present to the user.

### Error handling: the agent reads your failures

Errors don't just stop the workflow — they go back to the LLM, which usually corrects its call and retries. Use that:

```javascript
// Option A: throw — n8n surfaces the message to the agent
if (!isFinite(price)) throw new Error('price must be a number, e.g. 439900');

// Option B: return an error string — agent reads it like any tool result
if (!isFinite(price)) return JSON.stringify({ error: 'price must be a number, e.g. 439900' });
```

Either way, write error messages **for the LLM**: state what was wrong and what a valid call looks like. A bare `throw new Error('invalid input')` wastes the retry; an instructive message usually fixes the next call.

---

## Tool Name and Description

These fields are NOT documentation — they are the **tool contract the LLM sees**. Treat them as prompt engineering.

### Name
- Must match `[A-Za-z0-9_]+` (v1.1+). No spaces, no hyphens, no emoji.
- Use a verb-y descriptive name: `calculate_car_loan`, `get_weather`, `search_orders`.
- The agent calls the tool by this name. `Code Tool` (the default) is useless — the agent won't know when to call it.

### Description
- Explain **when** to use it and **what** to send.
- If unstructured mode, **include an example of the JSON string** the LLM should send.
- If structured mode, the schema speaks for itself — just describe purpose.

**Unstructured example (JSON-in-string pattern):**
```
Deterministiskt beräknar månadskostnad för billån. Anropa med EN JSON-sträng:
{"price":439900,"down_payment":87980,"interest_rate":6.95,"months":36,"residual_percent":50}
Fält: price (SEK), down_payment (SEK), interest_rate (% per år), months, residual_percent (0-99).
```

**Structured example (schema-defined):**
```
Deterministically computes the monthly car-loan payment given price, down payment, 
annual interest rate, term, and residual percent. Use whenever the user asks for 
monthly cost, total credit cost, or loan breakdown.
```

---

## Top Errors and Fixes

### Error 1: `"There was an error: 'Cannot assign to read only property \"name\" of object: Error: No execution data available'"`

**Cause**: you called `$fromAI()` inside the Code Tool sandbox.