n8n-code-python

Write Python code in n8n Code nodes. Use when writing Python in n8n, using _input/_json/_node syntax, working with standard library, or need to understand Python limitations in n8n Code nodes. Use this skill when the user specifically requests Python for an n8n Code node. Note — JavaScript is recommended for 95% of use cases — only use Python when the user explicitly prefers it or the task requires Python-specific standard library capabilities (regex, hashlib, statistics). EXCEPTION — for Python in the AI-agent-callable Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode), use the n8n-code-tool skill instead (input is _query, return must be a string).

Quality

76%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/n8n-code-python/SKILL.md

Quality

Content

65%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with executable examples and good structure, but loses points for repeated JavaScript-first messaging, the absence of a validation feedback loop for batch operations, and four referenced bundle files that are missing from the directory.

Suggestions

Create the four referenced bundle files (DATA_ACCESS.md, COMMON_PATTERNS.md, ERROR_PATTERNS.md, STANDARD_LIBRARY.md) or remove the inline 'See' links so navigation is functional.

Consolidate the JavaScript-first recommendation into a single section; it is currently restated in the description, the 'JavaScript First' section, 'Essential Rules', and the 'When to Use Python vs JavaScript' section.

Add an explicit validate → fix → retry feedback loop for batch transformations (e.g., run on a single item, inspect output, then process all) to lift workflow clarity above the batch-operation cap of 3.

Dimension	Reasoning	Score
Conciseness	Mostly efficient and free of beginner-concept padding, but the JavaScript-first recommendation is repeated across four sections and return-format rules are restated multiple times, adding tokens that could be trimmed.	3 / 5
Actionability	Copy-paste-ready, executable code throughout — Quick Start template, mode examples, data-access patterns, wrong-vs-right webhook and return-format snippets, and best-practice blocks — covering the common cases comprehensively.	5 / 5
Workflow Clarity	A pattern catalog with a Top-5 errors list and a deploy checklist, but no explicit validate → fix → retry feedback loop for the batch/transformation operations it enables; per the batch-operation cap this cannot exceed 3.	3 / 5
Progressive Disclosure	References to DATA_ACCESS.md, COMMON_PATTERNS.md, ERROR_PATTERNS.md, and STANDARD_LIBRARY.md are clearly signaled and one level deep, but none of these bundle files actually exist in the skill directory, so navigation is not functional.	3 / 5
	Total	14 / 20 Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is strong: it states concrete capabilities, gives an explicit 'Use this skill when...' trigger, and carves out clear boundaries against the sibling tool skill and JavaScript. Minor tightening of the action list could move specificity to a perfect score.

Dimension	Reasoning	Score
Specificity	Names the domain and several concrete actions — 'Write Python code in n8n Code nodes', 'using _input/_json/_node syntax', 'working with standard library', 'understand Python limitations' — but the actions are interleaved with recommendation/exception caveats rather than a comprehensive action list.	4 / 5
Completeness	Explicitly answers both what ('Write Python code in n8n Code nodes... syntax, standard library, limitations') and when ('Use this skill when the user specifically requests Python for an n8n Code node') with concrete trigger phrases and an explicit exception clause.	5 / 5
Trigger Term Quality	Good natural keyword coverage including 'Python in n8n', 'n8n Code node', 'standard library', and concrete module triggers 'regex, hashlib, statistics'; a few user-natural synonyms are absent and the language skews slightly technical.	4 / 5
Distinctiveness Conflict Risk	Clear niche (Python in n8n Code nodes) with an explicit boundary against the sibling n8n-code-tool skill and an explicit JS-recommendation guardrail, minimizing wrong-skill triggering.	5 / 5
	Total	18 / 20 Passed

Validation

87%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (502 lines); consider splitting into references/ and linking	Warning
relative_links	Relative link issues: 11 missing	Warning

	Total	14 / 16 Passed

Repository: czlonkowski/n8n-skills
Path: skills/n8n-code-python/SKILL.md
Commit: 0296522

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.