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-lambdagit clone --depth 1 https://github.com/sanjeed5/awesome-cursor-rules-mdcWhat 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 | $0.01365 | $0.01365 |
| Opus 5 | $0.00682 | $0.00682 |
| Sonnet 5 | $0.00273 | $0.00273 |
| Haiku 4.5 | $0.00136 | $0.00136 |
Grade A, and why
aws-lambda 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
aws-lambda Best Practices
This guide outlines the definitive best practices for developing AWS Lambda functions. Adhere to these principles to build reliable, cost-effective, and secure serverless applications.
Code Organization and Structure
1. Single Responsibility Principle: Each Lambda function must perform one distinct task. Decompose complex workflows into smaller, focused functions orchestrated by services like AWS Step Functions.
2. Initialize Outside the Handler: Leverage execution environment reuse by initializing SDK clients, database connections, and heavy dependencies in the global scope.
❌ BAD:
import boto3
def handler(event, context):
s3 = boto3.client('s3') # Initialized on every invocation
# ...
✅ GOOD:
import boto3
s3 = boto3.client('s3') # Initialized once per execution environment
def handler(event, context):
# s3 client is reused across invocations
# ...
3. Use Lambda Layers for Shared Code: Keep deployment packages small and promote code reuse for common libraries and dependencies.
4. Configuration via Environment Variables: Never hardcode operational parameters. Use environment variables for dynamic configuration. For sensitive data, use AWS Secrets Manager or AWS Systems Manager Parameter Store.
5. Structured JSON Logging: Output logs in JSON format to CloudWatch. This makes logs easily queryable and analyzable. Use aws-lambda-powertools Logger utility.
❌ BAD:
print(f"Processing event: {event}")
✅ GOOD:
from aws_lambda_powertools import Logger
logger = Logger()
@logger.inject_lambda_context
def handler(event, context):
logger.info("Processing event", event=event)
# ...
6. Infrastructure as Code (AWS CDK v2): Define your Lambda functions and their surrounding infrastructure (API Gateway, DynamoDB, IAM roles) using AWS CDK v2. This ensures version control, repeatability, and safe deployments.
✅ GOOD:
# Example using AWS CDK v2 (Python)
from aws_cdk import Stack, aws_lambda as lambda_
from constructs import Construct
class MyLambdaStack(Stack):
def __init__(self, scope: Construct, construct_id: str, **kwargs) -> None:
super().__init__(scope, construct_id, **kwargs)
lambda_.Function(self, "MyHandler",
runtime=lambda_.Runtime.PYTHON_3_12,
handler="index.handler",
code=lambda_.Code.from_asset("lambda"), # 'lambda' directory contains index.py
environment={
"TABLE_NAME": "MyTable",
},
# Add more configurations like memory, timeout, IAM roles
)
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 · 173 lines · 0 tokens per session scan A 787cba061f9c
aws-lambda is a cursor rule published in the GitHub repository sanjeed5/awesome-cursor-rules-mdc (3,570 stars, last pushed 3mo ago), licensed CC0-1.0. It adds 1,365 tokens to every session, about $0.0068 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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