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Lambda

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itsmostafa
lambda

AWS Lambda serverless functions for event-driven compute. Use when creating functions, configuring triggers, debugging invocations, optimizing cold starts, setting up event source mappings, or managing layers.

Overview

Publisheritsmostafa
Repositoryaws-agent-skills
Skill namelambda
Stars
1.2K
Forks
445
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by itsmostafa on GitHub. Read the source before you install it.

Installation

Install the Lambda AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/itsmostafa/aws-agent-skills/tree/main/skills/lambda
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/itsmostafa/aws-agent-skills.git /tmp/aws-agent-skills
mkdir -p .claude/skills
cp -r /tmp/aws-agent-skills/skills/lambda .claude/skills/lambda
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Lambda in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Lambda on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Lambda is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AWS Lambda

AWS Lambda runs code without provisioning servers. You pay only for compute time consumed. Lambda automatically scales from a few requests per day to thousands per second.

Table of Contents

Core Concepts

Function

Your code packaged with configuration. Includes runtime, handler, memory, timeout, and IAM role.

Invocation Types

TypeDescriptionUse Case
SynchronousCaller waits for responseAPI Gateway, direct invoke
AsynchronousFire and forgetS3, SNS, EventBridge
Poll-basedLambda polls sourceSQS, Kinesis, DynamoDB Streams

Execution Environment

Lambda creates execution environments to run your function. Components:

  • Cold start: New environment initialization
  • Warm start: Reusing existing environment
  • Handler: Entry point function
  • Context: Runtime information

Layers

Reusable packages of libraries, dependencies, or custom runtimes (up to 5 per function).

Common Patterns

Create a Python Function

AWS CLI:

bash
# Create deployment package
zip function.zip lambda_function.py

# Create function
aws lambda create-function \
  --function-name MyFunction \
  --runtime python3.12 \
  --role arn:aws:iam::123456789012:role/lambda-role \
  --handler lambda_function.handler \
  --zip-file fileb://function.zip \
  --timeout 30 \
  --memory-size 256

# Update function code
aws lambda update-function-code \
  --function-name MyFunction \
  --zip-file fileb://function.zip

boto3:

python
import boto3
import zipfile
import io

lambda_client = boto3.client('lambda')

# Create zip in memory
zip_buffer = io.BytesIO()
with zipfile.ZipFile(zip_buffer, 'w') as zf:
    zf.writestr('lambda_function.py', '''
def handler(event, context):
    return {"statusCode": 200, "body": "Hello"}
''')
zip_buffer.seek(0)

# Create function
lambda_client.create_function(
    FunctionName='MyFunction',
    Runtime='python3.12',
    Role='arn:aws:iam::123456789012:role/lambda-role',
    Handler='lambda_function.handler',
    Code={'ZipFile': zip_buffer.read()},
    Timeout=30,
    MemorySize=256
)

Add S3 Trigger

bash
# Add permission for S3 to invoke Lambda
aws lambda add-permission \
  --function-name MyFunction \
  --statement-id s3-trigger \
  --action lambda:InvokeFunction \
  --principal s3.amazonaws.com \
  --source-arn arn:aws:s3:::my-bucket \
  --source-account 123456789012

# Configure S3 notification (see S3 skill)

Add SQS Event Source

bash
aws lambda create-event-source-mapping \
  --function-name MyFunction \
  --event-source-arn arn:aws:sqs:us-east-1:123456789012:my-queue \
  --batch-size 10 \
  --maximum-batching-window-in-seconds 5

Environment Variables

bash
aws lambda update-function-configuration \
  --function-name MyFunction \
  --environment "Variables={DB_HOST=mydb.cluster-xyz.us-east-1.rds.amazonaws.com,LOG_LEVEL=INFO}"

Create and Attach Layer

bash
# Create layer
zip -r layer.zip python/

aws lambda publish-layer-version \
  --layer-name my-dependencies \
  --compatible-runtimes python3.12 \
  --zip-file fileb://layer.zip

# Attach to function
aws lambda update-function-configuration \
  --function-name MyFunction \
  --layers arn:aws:lambda:us-east-1:123456789012:layer:my-dependencies:1

Invoke Function

bash
# Synchronous invoke
aws lambda invoke \
  --function-name MyFunction \
  --payload '{"key": "value"}' \
  response.json

# Asynchronous invoke
aws lambda invoke \
  --function-name MyFunction \
  --invocation-type Event \
  --payload '{"key": "value"}' \
  response.json

CLI Reference

Function Management

CommandDescription
aws lambda create-functionCreate new function
aws lambda update-function-codeUpdate function code
aws lambda update-function-configurationUpdate settings
aws lambda delete-functionDelete function
aws lambda list-functionsList all functions
aws lambda get-functionGet function details

Invocation

CommandDescription
aws lambda invokeInvoke function
aws lambda invoke-asyncAsync invoke (deprecated)

Event Sources

CommandDescription
aws lambda create-event-source-mappingAdd event source
aws lambda list-event-source-mappingsList mappings
aws lambda update-event-source-mappingUpdate mapping
aws lambda delete-event-source-mappingRemove mapping

Permissions

CommandDescription
aws lambda add-permissionAdd resource-based policy
aws lambda remove-permissionRemove permission
aws lambda get-policyView resource policy

Best Practices

Performance

  • Right-size memory: More memory = more CPU = faster execution
  • Minimize cold starts: Keep functions warm, use Provisioned Concurrency
  • Optimize package size: Smaller packages deploy faster
  • Use layers for shared dependencies
  • Initialize outside handler: Reuse connections across invocations
python
# GOOD: Initialize outside handler
import boto3
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('MyTable')

def handler(event, context):
    # Reuses existing connection
    return table.get_item(Key={'id': event['id']})

Security

  • Least privilege IAM roles — only grant needed permissions
  • Use Secrets Manager for sensitive data
  • Enable VPC only if needed (adds latency)
  • Encrypt environment variables with KMS

Cost Optimization

  • Set appropriate timeout — don't use max 15 minutes unnecessarily
  • Use ARM architecture (Graviton2) for 34% better price/performance
  • Batch process where possible
  • Use Reserved Concurrency to limit costs

Reliability

  • Configure DLQ for async invocations
  • Handle retries — async events retry twice
  • Make handlers idempotent
  • Use structured logging

Troubleshooting

Timeout Errors

Symptom: Task timed out after X seconds

Causes:

  • Function takes longer than timeout
  • Network call to unreachable resource
  • VPC configuration issues

Debug:

bash
# Check function configuration
aws lambda get-function-configuration \
  --function-name MyFunction \
  --query "Timeout"

# Increase timeout
aws lambda update-function-configuration \
  --function-name MyFunction \
  --timeout 60

Out of Memory

Symptom: Function crashes with memory error

Fix:

bash
aws lambda update-function-configuration \
  --function-name MyFunction \
  --memory-size 512

Cold Start Latency

Causes:

  • Large deployment package
  • VPC configuration
  • Many dependencies to load

Solutions:

  • Use Provisioned Concurrency
  • Reduce package size
  • Use layers for dependencies
  • Consider Graviton2 (ARM)
bash
# Enable Provisioned Concurrency
aws lambda put-provisioned-concurrency-config \
  --function-name MyFunction \
  --qualifier LIVE \
  --provisioned-concurrent-executions 5

Permission Denied

Symptom: AccessDeniedException

Debug:

bash
# Check execution role
aws lambda get-function-configuration \
  --function-name MyFunction \
  --query "Role"

# Check role policies
aws iam list-attached-role-policies \
  --role-name lambda-role

VPC Connectivity Issues

Symptom: Cannot reach internet or AWS services

Causes:

  • No NAT Gateway for internet access
  • Missing VPC endpoint for AWS services
  • Security group blocking outbound

Solutions:

  • Add NAT Gateway for internet
  • Add VPC endpoints for AWS services
  • Check security group rules

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Lambda AI skill do?

AWS Lambda serverless functions for event-driven compute. Use when creating functions, configuring triggers, debugging invocations, optimizing cold starts, setting up event source mappings, or managing layers.

Why use Lambda on TypingMind?

Because you install it once and use it with any model. Lambda is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Lambda in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/itsmostafa/aws-agent-skills/tree/main/skills/lambda. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Lambda?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Lambda?

As many as you like. As long as a model supports skills, you can use Lambda with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Lambda AI skill free?

Yes. It is published on GitHub by itsmostafa under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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