awesome-cursor-rules-mdc is a generator that creates Cursor MDC rule files from structured library information, using semantic search and language models to gather and organize guidance. Developers use it to produce reusable rules for libraries in Cursor, and the catalogue includes 200 of those rules.
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/sanjeed5/awesome-cursor-rules-mdcWrote 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/sanjeed5/awesome-cursor-rules-mdc/gcp)<a href="https://agentmods.dev/rules/sanjeed5/awesome-cursor-rules-mdc/gcp"><img src="https://agentmods.dev/badge/rules/sanjeed5/awesome-cursor-rules-mdc/gcp.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 | $0.01812 | $0.01812 |
| Opus 5 | $0.00906 | $0.00906 |
| Sonnet 5 | $0.00362 | $0.00362 |
| Haiku 4.5 | $0.00181 | $0.00181 |
Grade A, and why
gcp 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 4d 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 — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gcp Best Practices
Adhering to these guidelines ensures your GCP applications are robust, secure, and performant. Treat these as non-negotiable standards.
Code Organization and Structure
1. Adhere to Google's Language Style Guides
Consistency is paramount. Always follow the official Google Style Guides for your chosen language. This improves readability and maintainability across the team.
Guideline: Integrate linting and formatting tools (e.g., Black for Python, Prettier for JS) configured with Google's style.
2. Infrastructure as Code (IaC) is Mandatory
Provision and manage all GCP resources using IaC. This ensures declarative, version-controlled, and auditable infrastructure. Terraform is the default choice.
Guideline: Treat your infrastructure code with the same rigor as application code.
❌ BAD: Manual console configuration, gcloud commands for provisioning.
✅ GOOD: Terraform for all resource definitions.
# main.tf
resource "google_project_service" "compute_api" {
project = var.project_id
service = "compute.googleapis.com"
disable_on_destroy = false
}
resource "google_compute_instance" "default" {
project = var.project_id
zone = "us-central1-a"
name = "my-app-instance"
machine_type = "e2-medium"
boot_disk {
initialize_params {
image = "debian-cloud/debian-11"
}
}
network_interface {
network = "default"
}
}
Common Patterns and Anti-patterns
1. Write Idempotent Functions and Services
Your functions and services must produce the same result regardless of how many times they are called with the same input. This is critical for retries and distributed systems.
❌ BAD: Non-idempotent operation.
# Function that decrements a counter without checking state
def process_order(order_id):
# This will decrement the counter every time it's called
db.update_counter(order_id, -1)
✅ GOOD: Idempotent operation using a transaction or state check.
# Function that processes an order idempotently
def process_order_idempotent(order_id):
# Use a transaction or check for existing processed state
if not db.order_processed(order_id):
db.process_order(order_id)
db.mark_order_processed(order_id)
else:
print(f"Order {order_id} already processed, skipping.")
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.
- 4d ago First seen · 224 lines · 1,812 tokens per session scan A 43915fe4e1f3
gcp is a cursor rule published in the GitHub repository sanjeed5/awesome-cursor-rules-mdc (3,571 stars, last pushed 3mo ago), licensed CC0-1.0. It adds 1,812 tokens to every session, about $0.0091 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 2026-09-03.
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