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.
npx agentmods add rules/sanjeed5/awesome-cursor-rules-mdc/aws-rdsgit 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/aws-rds)<a href="https://agentmods.dev/rules/sanjeed5/awesome-cursor-rules-mdc/aws-rds"><img src="https://agentmods.dev/badge/rules/sanjeed5/awesome-cursor-rules-mdc/aws-rds.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 | $0.02798 | $0.02798 |
| Opus 5 | $0.01399 | $0.01399 |
| Sonnet 5 | $0.00560 | $0.00560 |
| Haiku 4.5 | $0.00280 | $0.00280 |
Grade A, and why
aws-rds 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 6d 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 — 385 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aws-rds Best Practices
This guide outlines the definitive best practices for interacting with and managing AWS RDS instances. Adhere to these guidelines to ensure your database operations are secure, performant, and maintainable.
1. Security Best Practices
Security is paramount. Always assume your database is a target.
1.1. Manage Credentials with AWS Secrets Manager
Never hardcode database credentials or store them in environment variables directly. Use AWS Secrets Manager with automatic rotation enabled.
❌ BAD:
# app.py
DB_USER = os.getenv("DB_USER")
DB_PASS = os.getenv("DB_PASS")
conn = psycopg2.connect(user=DB_USER, password=DB_PASS, host=DB_HOST)
✅ GOOD:
import boto3
import json
def get_secret(secret_name):
client = boto3.client('secretsmanager')
response = client.get_secret_value(SecretId=secret_name)
return json.loads(response['SecretString'])
# app.py
secret = get_secret("your-rds-db-credentials")
DB_USER = secret['username']
DB_PASS = secret['password']
DB_HOST = secret['host']
conn = psycopg2.connect(user=DB_USER, password=DB_PASS, host=DB_HOST)
Context: Secrets Manager handles rotation, encryption, and secure retrieval, significantly reducing the risk of credential compromise.
1.2. Enforce Least Privilege with IAM
Control access to RDS API actions (create, modify, delete clusters, security groups, parameter groups) using IAM identities, not the root account. Grant only the minimum permissions required. Organize permissions with IAM groups.
❌ BAD:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": "rds:*",
"Resource": "*"
}
]
}
Context: This grants full access to all RDS resources, a massive security risk.
✅ GOOD:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"rds:DescribeDBInstances",
"rds:DescribeDBSnapshots",
"rds:Connect"
],
"Resource": "*"
},
{
"Effect": "Allow",
"Action": [
"rds:ModifyDBInstance",
"rds:DeleteDBInstance"
],
"Resource": "arn:aws:rds:REGION:ACCOUNT_ID:db:my-specific-app-db"
}
]
}
Context: This policy grants read-only access to all RDS resources and specific modification/deletion rights to a single, named DB instance.
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.
- 6d ago First seen · 385 lines · 0 tokens per session scan A 84f8995085a5
aws-rds 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 2,798 tokens to every session, about $0.0140 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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