Model or dataset
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haunchen/n8n-skills

n8n-skills: a generated Claude skill pack for n8n node knowledge

Designed specifically for AI assistants, the n8n Workflow Automation Skills Suite.

399 stars28 forksTypeScriptNOASSERTION

At a glance

What is it?
The haunchen/n8n-skills repository does not run n8n workflows. It builds a documentation skill pack from n8n packages so Claude can answer node questions, and the README states it targets n8n v2.38.7.
Who is it for?
Adopt n8n-skills if you already write n8n workflows and use Claude, and you want node lookup to happen inside the chat instead of a browser tab. Skip it if you need the assistant to open a live n8n instance, or if you run a node version other than the one the README pins, v2.38.7.
Can I use it commercially?
Check first. The repository uses a licence we do not classify automatically, so read its LICENSE file before any commercial use.
Is it still maintained?
Yes. The repository last received commits 3 days ago.
What is it written in?
Mainly TypeScript, according to GitHub's language statistics.

Answers come from the project's GitHub data, last synced on September 15, 2026, and from our analysis. They are not legal advice.

DEEP OPEN-SOURCE ANALYSIS

What n8n-skills is, and who the README is written for

n8n-skills is not an n8n node, an MCP server or a plugin you install into n8n itself. It is a generator: a TypeScript project that reads n8n node packages, APIs and documentation, and emits a skill pack that Claude loads. The README's own framing is blunt about the audience. It lists AI assistant developers on Claude Code, Claude.ai web users, and Claude Desktop users, then adds automation engineers who want AI-assisted workflow design and people who need quick node lookups.

The problem it addresses is narrow and real. If you ask a general assistant how to wire a Gmail node to a Code node, you get plausible-sounding node names and parameters that may not exist in your installed version. n8n-skills replaces that recall with generated reference files shipped alongside a SKILL.md. The README states the pack covers 545 nodes and 20 curated templates across categories such as input, output, transform, trigger, organization, misc, community and templates.

One line in the README deserves attention before anything else: "Supported n8n version: v2.38.7". That is a pin, not a range. The knowledge in the pack was generated against that version, and the repository's own dependencies reflect it, with n8n at ^2.38.7 and n8n-nodes-base at ^2.15.1 in package.json. If you run a much older or much newer n8n, the generated documentation is a snapshot of someone else's install.

How the generator works: five layers and a priority ranking

The README describes a five-layer modular architecture: collectors, parsers, organizers, generators and build scripts. Data flows in one direction. Collectors pull information from n8n NPM packages, APIs and documentation. Parsers turn that into structured data. Organizers group it, which is where the category folders in the output come from. Generators write the markdown resources and the main SKILL.md. Build scripts tie it together.

The project states it is built on the n8n-mcp architecture, converted into a skill pack generator, with priority ranking, node grouping and documentation integration added. The ranking is the interesting part: the README calls it a multi-dimensional priority ranking system that ensures the most useful information is presented first. In practice that matters because a skill pack is context, and context is finite. If all 545 nodes were dumped in equally, the assistant would spend its window on obscure nodes. Ranking is the mechanism that decides what survives.

The repository layout matches the description. There is a src/ directory for the layers, scripts/ for the build entry points, config/ for settings, data/ with a cache that the clean script preserves only community-nodes.json from, tests/ with Jest, and a website/ directory. The examples/ folder shows the pipeline being driven piece by piece: api-collector-example.ts, parser-usage.ts, use-organizers.ts, generate-resources.ts and generate-skill.ts. Those filenames are the clearest map of the data flow you will get without reading the source.

package.json exposes the same pipeline as npm scripts. The build is plain tsc. build:full runs the TypeScript build and then node dist/scripts/build.js. update runs the build and then dist/scripts/update-n8n-data.js, with update:check adding --dry-run. There are separate update:community and update:community:check scripts, and a validate script that runs dist/scripts/validate-output.js. A dry-run flag existing for both update paths suggests the authors expect you to inspect changes before writing them.

Installing the skill pack in Claude Code

The README's installation path starts outside npm. You go to the GitHub Releases page and download n8n-skills-{version}.zip, then extract it. After extraction the structure is a top-level SKILL.md plus a resources/ directory containing input, output, transform, trigger, organization, misc, community and templates. The npm package exists for people regenerating the pack, not for people consuming it.

For Claude Code, the README says to create a skills directory in your project root and copy the extracted contents into it. Two commands cover it:

bash
mkdir -p .claude/skills/n8n-skills

The second command copies the extracted SKILL.md and resources/ into that directory. The README writes it as:

bash
cp -r n8n-skills/* .claude/skills/n8n-skills/

The resulting layout the README expects is your-project/.claude/skills/n8n-skills/ containing SKILL.md and resources/. Verification is conversational rather than mechanical: the README says to ask Claude Code "List available n8n nodes" and treat a correct answer as proof the skill was invoked. That is a weak test, and worth knowing before you debug a silent failure. If nothing loads, the README offers no diagnostic step beyond checking the directory structure.

For Claude.ai web and Claude Desktop, the flow is upload-based. Open Settings, find the Capabilities section, and in Desktop also the Skills subsection, then click Upload skill and select the zip. After the upload completes, n8n-skills appears in the list; if it is not enabled, you click to enable it. Then you return to the conversation and ask an n8n question. The README's own example prompts are ordinary questions: "What are the main features of the HTTP Request node?", "How to send email using the Gmail node?", "Which nodes can connect to Google Sheets?"

The limitation the README does not solve: it is a snapshot, not a live n8n

The clearest boundary is that n8n-skills knows nothing about your instance. It does not connect to your n8n, does not list the workflows you have built, and does not read your credentials or your execution history. It answers from generated files. If you have installed a community node that is not in the pack, the assistant will not know it exists, and it may answer confidently from the 545 nodes it does have.

Version drift is the second boundary. The README pins v2.38.7, and the pack is generated against the packages at that version. n8n ships often. The repository's own release cadence, v2.20.0 on 2026-08-17, v2.21.0 on 2026-08-23 and v2.22.0 on 2026-08-30, shows the pack is regenerated regularly, but each release is still a snapshot. The last push to the repository was on 2026-09-13, so the project is not dormant, but that says nothing about whether the pack matches your install today.

The third boundary is more structural. The README claims node compatibility analysis and node configuration validation. Those are checks against generated metadata, not against a running n8n. A workflow the assistant says is valid can still fail at execution time because of a credential, a rate limit, or a node behaviour the documentation does not capture. Treat the output as a well-informed draft, not as a validated workflow.

n8n-mcp and other ways to give an assistant n8n knowledge

The README states n8n-skills is built on the n8n-mcp architecture, so the two are related rather than rivals. The difference is in what reaches the model. An MCP server exposes tools that an assistant calls at runtime, which typically means a live process answering queries. n8n-skills converts the same kind of knowledge into static skill files that Claude loads as context. Static files cannot go stale mid-session and do not need a running process; a live server can reflect the instance it is connected to and can answer about nodes added after the pack was generated.

That trade-off decides the choice. If you want the assistant to inspect or modify workflows in a specific n8n instance, a skill pack is the wrong tool, because the README describes no such capability. If you want node reference material available offline, inside a chat, with no server to keep running, the generated pack is the simpler shape.

The other alternative is doing nothing and relying on the assistant's built-in n8n knowledge. That is free and requires no installation, but it is exactly the situation the project exists to fix: parameters and node names recalled from training data rather than read from a versioned source. The cost of the pack is one zip download and a copy command.

Regenerating the pack yourself, and what that costs

If you want the pack to match a different n8n version, the repository is the generator, and package.json shows how to drive it. The update scripts are the entry point, and both support a dry run:

bash
npm run update:check

That script builds the project and runs node dist/scripts/update-n8n-data.js --dry-run. The community package path is separate:

bash
npm run update:community:check

After a real update, validate runs the build and then dist/scripts/validate-output.js, which is the closest thing to a correctness check the repository exposes. The clean script deletes dist/ and output/ and clears data/cache except community-nodes.json, which tells you the community node list is treated as expensive to rebuild.

The maintenance cost is real. Regenerating means installing n8n, n8n-core, n8n-nodes-base, n8n-workflow and @n8n/n8n-nodes-langchain at the versions you care about, and the README gives no guidance on which versions are compatible with the generator itself. The dependency on simple-git suggests the build touches git state, which is another thing that can break in a fresh checkout.

On licensing, package.json declares MIT, but GitHub reports the repository licence as NOASSERTION, meaning the platform could not classify the LICENSE file automatically. The repository also carries ATTRIBUTIONS.md and ATTRIBUTIONS.en.md, which matters because the pack is generated from n8n packages and documentation that carry their own terms. If you redistribute the generated pack, read the LICENSE file and the attribution documents rather than trusting the package.json field.

Editorial conclusion

Adopt n8n-skills if you already write n8n workflows and use Claude, and you want node lookup to happen inside the chat instead of a browser tab. Skip it if you need the assistant to open a live n8n instance, or if you run a node version other than the one the README pins, v2.38.7. Before trusting it, open the release zip and read SKILL.md to confirm the node coverage matches the n8n version you actually run, and check the LICENSE file, because GitHub reports the licence as NOASSERTION even though package.json says MIT.

Frequently asked questions

What are skills in n8n and how are they used?

In this project, a skill is a folder containing SKILL.md plus a resources/ directory of generated node documentation that Claude loads as context. The README describes installing it into .claude/skills/n8n-skills/ for Claude Code, or uploading the release zip through the Capabilities section on Claude.ai and Claude Desktop.

What is n8n skills?

n8n-skills is a generator that produces a Claude skill pack from n8n node packages, APIs and documentation. The README states the output covers 545 nodes and 20 curated templates, and that it supports Claude Code, Claude.ai Web and Claude Desktop.

How do n8n skills and MCP relate?

The README states the project is built on the n8n-mcp architecture and converted into a skill pack generator, adding priority ranking, node grouping and documentation integration. The result is static skill files rather than a running MCP server, so it answers from generated documentation instead of a live n8n instance.

Official sources

  1. haunchen/n8n-skills on GitHub
  2. Issues
  3. Project website
  4. README
  5. Releases
Community notes

Community notes