home / skills / jeremylongshore / claude-code-plugins-plus-skills / lambda-layer-creator

lambda-layer-creator skill

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/skills/13-aws-skills/lambda-layer-creator

This skill helps you create production-ready lambda layer configurations and best-practice guidance for AWS projects.

npx playbooks add skill jeremylongshore/claude-code-plugins-plus-skills --skill lambda-layer-creator

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: "lambda-layer-creator"
description: |
  Create lambda layer creator operations. Auto-activating skill for AWS Skills.
  Triggers on: lambda layer creator, lambda layer creator
  Part of the AWS Skills skill category. Use when working with lambda layer creator functionality. Trigger with phrases like "lambda layer creator", "lambda creator", "lambda".
allowed-tools: "Read, Write, Edit, Bash(aws:*)"
version: 1.0.0
license: MIT
author: "Jeremy Longshore <[email protected]>"
---

# Lambda Layer Creator

## Overview

This skill provides automated assistance for lambda layer creator tasks within the AWS Skills domain.

## When to Use

This skill activates automatically when you:
- Mention "lambda layer creator" in your request
- Ask about lambda layer creator patterns or best practices
- Need help with amazon web services skills covering compute, storage, networking, serverless, and aws-specific best practices.

## Instructions

1. Provides step-by-step guidance for lambda layer creator
2. Follows industry best practices and patterns
3. Generates production-ready code and configurations
4. Validates outputs against common standards

## Examples

**Example: Basic Usage**
Request: "Help me with lambda layer creator"
Result: Provides step-by-step guidance and generates appropriate configurations


## Prerequisites

- Relevant development environment configured
- Access to necessary tools and services
- Basic understanding of aws skills concepts


## Output

- Generated configurations and code
- Best practice recommendations
- Validation results


## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |


## Resources

- Official documentation for related tools
- Best practices guides
- Community examples and tutorials

## Related Skills

Part of the **AWS Skills** skill category.
Tags: aws, lambda, s3, ec2, cloudformation

Overview

This skill automates creation and management of AWS Lambda layers to simplify packaging shared dependencies and binaries. It guides you through layer design, packaging, versioning, and deployment with production-ready code and configuration snippets. Use it to standardize dependencies, reduce deployment size, and speed up serverless development workflows.

How this skill works

The skill inspects your project layout and dependency declarations, then generates layer packages, build scripts, and deployment templates (CloudFormation, SAM, or Terraform). It validates layer contents against AWS limits and common best practices, suggests runtime-compatible paths, and produces versioned artifacts ready for publishing to AWS. It can also include CI/CD snippets for automated layer builds and releases.

When to use it

When you need to package shared libraries or native binaries for multiple Lambda functions
When optimizing deployment size by moving common dependencies into layers
When implementing reproducible layer builds and versioning for production
When creating layers for multiple runtimes (Python, Node.js, Java)
When adding CI/CD automation for layer publishing

Best practices

Keep layers small and focused on a single responsibility to avoid bloated packages
Include only runtime files and compiled artifacts; exclude dev dependencies and tests
Use semantic versioning for layer versions and reference ARNs in infrastructure templates
Validate compatibility with target runtimes and file layout (/python, /nodejs folders) before publishing
Automate builds and integrity checks in CI to prevent broken layer releases

Example use cases

Create a Python data-processing layer with numpy and pandas compiled for AWS Lambda
Package native binaries (FFmpeg, ImageMagick) into a layer for media processing functions
Generate CloudFormation/SAM templates that attach layer ARNs to multiple functions
Produce CI pipeline steps to build, test, and publish layer versions to AWS Lambda
Prepare multi-runtime layers and provide correct folder structure for Python and Node.js functions

FAQ

Can one layer be used by functions with different runtimes?

A single layer should target a specific runtime layout; create separate layers for different runtimes or include separate runtime folders (/python, /nodejs) and validate compatibility.

How do I keep layer size under AWS limits?

Exclude dev dependencies, compile only required native binaries, strip symbols, and consider splitting large dependencies into multiple focused layers.