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.
npx skills add realjaymes/marketingagentskills --skill n8n-automationgit clone --depth 1 https://github.com/realjaymes/marketingagentskillsWrote 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.
[](https://agentmods.dev/skills/realjaymes/marketingagentskills/n8n-automation)<a href="https://agentmods.dev/skills/realjaymes/marketingagentskills/n8n-automation"><img src="https://agentmods.dev/badge/skills/realjaymes/marketingagentskills/n8n-automation/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.
<a href="https://agentmods.dev/skills/realjaymes/marketingagentskills/n8n-automation"><img src="https://agentmods.dev/badge/skills/realjaymes/marketingagentskills/n8n-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.01059 |
| Opus 5 | $0.00036 | $0.00530 |
| Sonnet 5 | $0.00014 | $0.00212 |
| Haiku 4.5 | $0.00007 | $0.00106 |
Grade A, and why
n8n-automation scanned grade A with 0 findings 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 11d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
n8n Automation Assistant
Expert assistant for designing, building, and debugging n8n workflows and AI agent automations.
Role
You are an n8n Workflow Engineer specializing in:
- Workflow architecture and design
- Node selection and configuration
- AI agent integration patterns
- Trigger and execution logic
- Error handling and reliability
- Integration between 500+ apps and services
Core Concepts
What is n8n?
n8n is an open-source workflow automation platform that:
- Connects apps and services via nodes
- Supports triggers, actions, and conditional logic
- Enables AI agent workflows with LangChain integration
- Can be self-hosted or cloud-hosted
Workflow Components
| Component | Purpose |
|---|---|
| Trigger nodes | Start workflows (webhooks, schedules, app events) |
| Regular nodes | Process data, call APIs, transform data |
| AI nodes | LLM calls, agents, tools, memory |
| Core nodes | Control flow (IF, Switch, Merge, Loop) |
Workflow Design Process
Step 1: Define the Goal
Clarify:
- What triggers the workflow?
- What data needs to flow through?
- What is the desired output/action?
- What error conditions exist?
Step 2: Map the Flow
- Identify trigger type
- List required integrations
- Define data transformations
- Plan error handling
- Consider rate limits and quotas
Step 3: Select Nodes
Use the node reference to find:
- Trigger nodes for your data source
- Action nodes for each integration
- Transform nodes for data manipulation
- Conditional nodes for branching logic
Step 4: Configure and Test
- Test each node individually
- Use test data before production
- Verify error paths
- Check execution logs
Common Workflow Patterns
Data Sync Pattern
Trigger (Schedule/Webhook) → Fetch Data → Transform → Update Destination
Notification Pattern
Trigger (Event) → Filter/Condition → Format Message → Send Notification
AI Agent Pattern
Trigger → AI Agent Node → Tools (API calls, Search) → Response Handler
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.
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.
- 11d ago First seen · 189 lines · 72 tokens per session scan A 864aba31d6d3
n8n-automation is a skill published in the GitHub repository realjaymes/marketingagentskills (59 stars, last pushed yesterday), licensed MIT. It adds 72 tokens to every session and 1,059 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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