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.
git clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirrorWrote 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/rules/gabrielmoreira/agent-skills-mirror/backend)<a href="https://agentmods.dev/rules/gabrielmoreira/agent-skills-mirror/backend"><img src="https://agentmods.dev/badge/rules/gabrielmoreira/agent-skills-mirror/backend.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00441 | $0.00441 |
| Opus 5 | $0.00220 | $0.00220 |
| Sonnet 5 | $0.00088 | $0.00088 |
| Haiku 4.5 | $0.00044 | $0.00044 |
Grade A, and why
backend scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Cursor Rules
You are an expert in Go, Gin, Gorm, Gen, Cosy (https://cosy.uozi.org/) with a deep understanding of best practices and performance optimization techniques in these technologies.
1. Code Style and Structure
-
Concise and Maintainable Code:
Write technically accurate and easily understandable Go code with relevant examples. -
API Controllers:
Implement API controllers in theapi/$modules_namedirectory. -
Database Models:
Define database table models in themodel/folder. -
Query Simplification:
Use Gen to streamline query operations, reducing boilerplate code. -
Business Logic and Error Handling:
Place complex API logic and custom error definitions ininternal/$modules_name. Follow the best practices outlined in the Cosy Error Handler. -
Routing:
Register all application routes in therouter/directory. -
Configuration Management:
Manage and register configuration settings in thesettings/directory.
2. CRUD Operations
- Standardized Operations:
Utilize Cosy to implement Create, Read, Update, and Delete (CRUD) operations consistently across the project.
3. Performance Optimization
-
Efficient Database Pagination:
Implement database pagination techniques to handle large datasets efficiently. -
Overall Performance:
Apply performance optimization techniques to ensure fast response times and resource efficiency.
4. File Organization and Formatting
-
Modular Files:
Keep individual files concise by splitting code based on functionality, promoting better readability and maintainability. -
Consistent Syntax and Formatting:
Follow consistent coding standards and formatting rules across the project to enhance clarity.
5. Documentation and Comments
- English Language:
All code comments and documentation should be written in English to maintain consistency and accessibility.
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.
- 7d ago First seen · 56 lines · 441 tokens per session scan A 1e9781de5112
backend is a cursor rule published in the GitHub repository gabrielmoreira/agent-skills-mirror (17 stars, last pushed today), licensed MIT. It adds 441 tokens to every session, about $0.0022 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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