n8n-code-python

n8n-code-python is a skill for Claude Code, Codex from yuchenbigpen1/normies. It costs 52 tokens per session (4,565 once invoked), scanned A, a copy of n8n-code-python, Apache-2.0.

A guide to writing Python in n8n Code nodes, which are workflow steps that run custom code. It explains n8n's input and output format and the limits of its Python support.

In plain words
What is it for?
Reading workflow items, transforming JSON data, and returning results from Python Code nodes in n8n.
Why use it?
It helps avoid code that uses the wrong data structure or unsupported Python features, while reminding you when JavaScript may fit n8n better.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Reading workflow items, transforming JSON data, and returning results from Python Code nodes in n8n.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/yuchenbigpen1/normies/n8n-code-python
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add yuchenbigpen1/normies --skill n8n-code-python
Clone the repo
git clone --depth 1 https://github.com/yuchenbigpen1/normies

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for n8n-code-python

README.md
[![agentmods](https://agentmods.dev/badge/skills/yuchenbigpen1/normies/n8n-code-python/github.svg)](https://agentmods.dev/skills/yuchenbigpen1/normies/n8n-code-python)
Your own site
<a href="https://agentmods.dev/skills/yuchenbigpen1/normies/n8n-code-python"><img src="https://agentmods.dev/badge/skills/yuchenbigpen1/normies/n8n-code-python/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for n8n-code-python

Your own site · 80×15
<a href="https://agentmods.dev/skills/yuchenbigpen1/normies/n8n-code-python"><img src="https://agentmods.dev/badge/skills/yuchenbigpen1/normies/n8n-code-python.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,565 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 86% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.04565
Opus 5.5 $0.00021 $0.01826
Sonnet 5.5 $0.00010 $0.00913
Haiku 4.5 $0.00005 $0.00456

Measured 1mo ago against content hash fa65b75a3605, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

n8n-code-python scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

6. **Standard library only**: json, datetime, re, base64, hashlib, urllib.parse, math, random, statistics
Origin

This is a copy

86% identical to n8n-code-python — 367 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

packages/shared/assets/workspace-template/skills/n8n-code-python/SKILL.md · 749 lines

How it starts

The opening of the file, as written. The whole thing — 749 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Code Node (Beta)

Expert guidance for writing Python code in n8n Code nodes.


⚠️ Important: JavaScript First

Recommendation: Use JavaScript for 95% of use cases. Only use Python when:

  • You need specific Python standard library functions
  • You're significantly more comfortable with Python syntax
  • You're doing data transformations better suited to Python

Why JavaScript is preferred:

  • Full n8n helper functions ($helpers.httpRequest, etc.)
  • Luxon DateTime library for advanced date/time operations
  • No external library limitations
  • Better n8n documentation and community support

Quick Start

# Basic template for Python Code nodes
items = _input.all()

# Process data
processed = []
for item in items:
    processed.append({
        "json": {
            **item["json"],
            "processed": True,
            "timestamp": datetime.now().isoformat()
        }
    })

return processed

Essential Rules

  1. Consider JavaScript first - Use Python only when necessary
  2. Access data: _input.all(), _input.first(), or _input.item
  3. CRITICAL: Must return [{"json": {...}}] format
  4. CRITICAL: Webhook data is under _json["body"] (not _json directly)
  5. CRITICAL LIMITATION: No external libraries (no requests, pandas, numpy)
  6. Standard library only: json, datetime, re, base64, hashlib, urllib.parse, math, random, statistics

Mode Selection Guide

Same as JavaScript - choose based on your use case:

Run Once for All Items (Recommended - Default)

Use this mode for: 95% of use cases

  • How it works: Code executes once regardless of input count
  • Data access: _input.all() or _items array (Native mode)
  • Best for: Aggregation, filtering, batch processing, transformations
  • Performance: Faster for multiple items (single execution)
# Example: Calculate total from all items
all_items = _input.all()
total = sum(item["json"].get("amount", 0) for item in all_items)

return [{
    "json": {
        "total": total,
        "count": len(all_items),
        "average": total / len(all_items) if all_items else 0
    }
}]

Read the full file on GitHub · 749 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 749 lines · 52 tokens per session scan A fa65b75a3605

Subscribe to this mod's changes

n8n-code-python is a skill published in the GitHub repository yuchenbigpen1/normies (4 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 52 tokens to every session and 4,565 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 86% identical to n8n-code-python, differing in 367 lines, and is treated as a copy.

Related

Other skills, from other repositories

py-reviewer

Review selected Python code for typing, async and exception behavior, resource ownership, data access, framework boundaries, and concrete contract defects in the project's actual runtime.

RaNDoM6913/claude-code-superkit · 35 tokens

coding

A coding guide for writing and running Python programs in a sandbox. It requires scripts to be small and reproducible, with their actual output or errors reported.

bojieli/ai-agent-book · 18 tokens

neo4j-driver-python-skill

Neo4j Python Driver v6 — driver lifecycle, executequery, managed and explicit transactions, async (AsyncGraphDatabase), result handling, data type mapping, error handling, UNWIND batching, connection pool tuning, and causal consistency. Use when writing Python code that connects to Neo4j via GraphDatabase.driver…

neo4j-contrib/neo4j-skills · 186 tokens

generating-python-installer

Commercial-grade Python installer expert for Windows: Nuitka extreme compilation, dist slimming, DLL footprint analysis, and Inno Setup packaging to ship the smallest, fastest installers. Use when a Python app must ship as a minimal, fast-starting Windows installer; not for basic script-to-exe conversion. Relevant…

sehoon787/my-codex · 98 tokens

fastapi-async-microservices

Design and develop production-grade asynchronous microservices using FastAPI, Python 3.12+, Pydantic v2 Settings and Schemas, SQLAlchemy 2.0 async sessions, dependency injection, lifespan state management, structured JSON logging, and connection pooling. Trigger when building async Python APIs, microservices, or…

hamzabellouch/agent-skills · 77 tokens

dsp-audio-filter-effects

Apply digital signal processing (DSP) algorithms in Python and C++ for audio filtering (IIR, FIR, Butterworth, Chebyshev), spectral analysis via Fast Fourier Transform (FFT), dynamic range compression, and modulation effects. Trigger when developing audio DSP algorithms, sound effects, or analyzing audio signals.

hamzabellouch/agent-skills · 68 tokens