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/levifig/rails-instructions/hotwiregit clone --depth 1 https://github.com/levifig/rails-instructionsWhat 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 | $0.00000 | $0.01213 |
| Opus 5 | $0.00000 | $0.00607 |
| Sonnet 5 | $0.00000 | $0.00243 |
| Haiku 4.5 | $0.00000 | $0.00121 |
Grade A, and why
hotwire 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.
How it starts
The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rails Hotwire Guide
Core Philosophy
- Send HTML over the wire, not JSON - let the server do the rendering
- Achieve SPA-like speed without complex JavaScript frameworks
- Use progressive enhancement - functionality works without JavaScript
- Keep client-side logic minimal and server-side logic rich
- Embrace the simplicity of multi-page applications with the speed of SPAs
Turbo Drive Principles
- Enable fast page navigation without full page reloads automatically
- Intercept all clicks and form submissions by default
- Maintain scroll position and focus between navigations
- Cache pages intelligently for instant back/forward navigation
- Preserve JavaScript state between page visits
Turbo Drive Configuration
- Disable Turbo Drive selectively with
data-turbo="false" - Control navigation behavior with
data-turbo-actionattributes - Use
data-turbo-permanentto persist elements across navigations - Configure cache behavior with meta tags
- Handle navigation events for custom behavior
Turbo Frames Principles
- Decompose pages into independent segments that update separately
- Scope navigation to frame boundaries automatically
- Enable partial page updates without custom JavaScript
- Support lazy loading for performance optimization
- Maintain proper URL and history management
Turbo Frames Best Practices
- Use meaningful frame IDs that describe their content
- Keep frames focused on a single concern
- Lazy load below-the-fold content with
loading="lazy" - Break out of frames with
data-turbo-frame="_top"when needed - Cache frame responses independently for better performance
Turbo Streams Principles
- Update multiple page elements in a single response
- Support real-time updates via WebSockets or SSE
- Use semantic actions: append, prepend, replace, update, remove
- Target elements by ID for surgical updates
- Broadcast changes from models automatically
Turbo Streams Implementation
- Return Turbo Stream responses from form submissions
- Use
turbo_streamformat in controllers - Broadcast model changes with Action Cable
- Target multiple elements in one response
- Keep stream templates simple and focused
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 · 171 lines · 0 tokens per session scan A fbbbfa5f83e8
hotwire is a cursor rule published in the GitHub repository levifig/rails-instructions (54 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,213 tokens. 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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