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 agentmods add rules/technickai/ai-coding-config/n8n-workflowsgit clone --depth 1 https://github.com/TechNickAI/ai-coding-configWhat 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 | $0.00008 | $0.00271 |
| Opus 5 | $0.00004 | $0.00135 |
| Sonnet 5 | $0.00002 | $0.00054 |
| Haiku 4.5 | $0.00001 | $0.00027 |
Grade A, and why
n8n-workflows 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 2d 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.
What it actually says
n8n Workflows
Code Snippets
When creating code snippet functions:
- Use Python, not JavaScript
- Create them as separate files in the workflow directory
- This allows independent unit testing
- Edit Python directly and test it separately
Example structure:
workflows/
my-workflow/
process_data.py
test_process_data.py
agent_prompts.md
workflow.json
Agent Prompts
Put agent prompts in separate .md files for easy editing:
# Agent: Data Processor
## System Prompt
You are a data processing agent...
## User Prompt
Process the following data: {{ data }}
Workflow Assembly
Only at the end of a session, assemble the final .json workflow file by including:
- Python snippets where appropriate
- Agent prompts in the right nodes
Node Positioning
Pay attention to positioning nodes in the UI for good UX:
- Group related nodes together
- Use consistent spacing
- Create logical left-to-right flow
- Add sticky notes for documentation
Testing
Before assembling into JSON:
- Unit test all Python functions
- Validate all agent prompts
- Test error handling paths
- Verify data transformations
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.
- 2d ago First seen · 68 lines · 8 tokens per session scan A e054b26b9d99
n8n-workflows is a cursor rule published in the GitHub repository TechNickAI/ai-coding-config (24 stars, last pushed 2mo ago), licensed MIT. It adds 8 tokens to every session and 271 once invoked, about $0.0000 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.
Other cursor rules, from other repositories
infra-devops
Infrastructure, Cloud, Terraform, Docker & CI/CD Agent.
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
coolify-ai-docs
Master reference to all Coolify AI documentation in .ai/ directory.
typescript
Changes to these high-fan-out internals can affect every message, delta, element, or rerun. Keep work in them minimal, and benchmark changes with representative stress-test apps.
python_lib
Tips and guidelines specific to the development of the Streamlit Python library, not applicable to scripts and e2e tests.