AWS Serverless Eda
zxkane/aws-skills
AWS serverless and event-driven architecture expert based on Well-Architected Framework.
Build and deploy serverless functions on AWS Lambda. An agent skill from sickn33/agentic-awesome-skills.
$ npx skills add sickn33/agentic-awesome-skills --skill aws-lambda -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install sickn33/agentic-awesome-skills aws-lambda --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/aws-lambda .claude/skills/aws-lambda && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "aws-lambda" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/aws-lambda into .claude/skills/aws-lambda/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-lambda", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/aws-lambdaType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add sickn33/agentic-awesome-skills --skill aws-lambda -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install sickn33/agentic-awesome-skills aws-lambda --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/aws-lambda .agents/skills/aws-lambda && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "aws-lambda" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/aws-lambda into .agents/skills/aws-lambda/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-lambda", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill aws-lambda -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install sickn33/agentic-awesome-skills aws-lambda --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/aws-lambda .cursor/skills/aws-lambda && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "aws-lambda" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/aws-lambda into .cursor/skills/aws-lambda/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-lambda", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/sickn33/agentic-awesome-skills.git --path skills/aws-lambda--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add sickn33/agentic-awesome-skills --skill aws-lambda -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install sickn33/agentic-awesome-skills aws-lambda --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/aws-lambda .gemini/skills/aws-lambda && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "aws-lambda" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/aws-lambda into .gemini/skills/aws-lambda/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-lambda", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install sickn33/agentic-awesome-skills aws-lambdaInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add sickn33/agentic-awesome-skills --skill aws-lambda -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/aws-lambda .github/skills/aws-lambda && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "aws-lambda" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/aws-lambda into .github/skills/aws-lambda/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-lambda", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill aws-lambda -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install sickn33/agentic-awesome-skills aws-lambda --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/aws-lambda .opencode/skills/aws-lambda && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "aws-lambda" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/aws-lambda into .opencode/skills/aws-lambda/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-lambda", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
aws-lambdaBuild and deploy serverless functions on AWS Lambda. An agent skill from sickn33/agentic-awesome-skills.
AWS Lambda is an agent skill from sickn33/agentic-awesome-skills. Build and deploy serverless functions on AWS Lambda. Configure triggers, manage permissions, and optimize performance. Use when implementing serverless applications.
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires the relevant OS/platform tooling and privileged access where noted. Docs-only; helper scripts and templates not bundled.
It sits in Backend & APIs, covering Serverless and Performance optimization. It works with AWS Lambda. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.
Read from SKILL.md and the folder at commit 1e53ce2. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
awspipFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use aws and pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Requires the relevant OS/platform tooling and privileged access where noted. Docs-only; helper scripts and templates not bundled.
From compatibility in the SKILL.md frontmatter.
AWS Lambda loads about 3.3k tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 363 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from sickn33/agentic-awesome-skills at commit 1e53ce2, republished under its MIT licence (© sickn33). 363 words, ~3,277 tokens.
.claude/skills/aws-lambda/SKILL.md (or your agent's skills folder).Build serverless applications with AWS Lambda, covering function creation, event sources, layers, SAM templates, and cold start optimization.
lambda:*, iam:PassRole, logs:*, apigateway:*, s3:*# Create a deployment package
cd my-function
zip -r function.zip app.py
# Create the Lambda function
aws lambda create-function \
--function-name my-api-handler \
--runtime python3.12 \
--handler app.handler \
--role arn:aws:iam::123456789012:role/LambdaExecRole \
--zip-file fileb://function.zip \
--memory-size 256 \
--timeout 30 \
--environment 'Variables={STAGE=production,LOG_LEVEL=INFO}' \
--architectures arm64 \
--tracing-config Mode=Active \
--tags '{"Team":"backend","Environment":"production"}'
# Update function code
aws lambda update-function-code \
--function-name my-api-handler \
--zip-file fileb://function.zip
# Update function configuration
aws lambda update-function-configuration \
--function-name my-api-handler \
--memory-size 512 \
--timeout 60 \
--environment 'Variables={STAGE=production,LOG_LEVEL=WARNING}'
# Publish a version (immutable snapshot)
aws lambda publish-version \
--function-name my-api-handler \
--description "v1.2.0 - added rate limiting"
# Create an alias pointing to the version
aws lambda create-alias \
--function-name my-api-handler \
--name live \
--function-version 3
# Weighted alias for canary deployments (90% v3, 10% v4)
aws lambda update-alias \
--function-name my-api-handler \
--name live \
--function-version 4 \
--routing-config '{"AdditionalVersionWeights":{"3":0.9}}'# app.py - API Gateway handler with structured logging
import json
import logging
import os
logger = logging.getLogger()
logger.setLevel(os.environ.get("LOG_LEVEL", "INFO"))
def handler(event, context):
"""Handle API Gateway proxy event."""
logger.info("Request: %s %s", event["httpMethod"], event["path"])
try:
body = json.loads(event.get("body", "{}"))
result = process_request(body)
return {
"statusCode": 200,
"headers": {
"Content-Type": "application/json",
"X-Request-Id": context.aws_request_id
},
"body": json.dumps(result)
}
except ValueError as e:
logger.warning("Validation error: %s", e)
return {"statusCode": 400, "body": json.dumps({"error": str(e)})}
except Exception as e:
logger.exception("Unhandled error")
return {"statusCode": 500, "body": json.dumps({"error": "Internal server error"})}
def process_request(body):
return {"message": "OK", "data": body}# sqs_processor.py - SQS batch processor with partial failure reporting
import json
import logging
logger = logging.getLogger()
logger.setLevel("INFO")
def handler(event, context):
"""Process SQS messages with partial batch failure reporting."""
failed_ids = []
for record in event["Records"]:
try:
body = json.loads(record["body"])
logger.info("Processing message: %s", record["messageId"])
process_message(body)
except Exception as e:
logger.error("Failed message %s: %s", record["messageId"], e)
failed_ids.append(record["messageId"])
# Return failed items so only those get retried
return {
"batchItemFailures": [
{"itemIdentifier": msg_id} for msg_id in failed_ids
]
}
def process_message(body):
pass # your logic here# Build a layer for Python dependencies
mkdir -p layer/python
pip install requests boto3-stubs -t layer/python/
cd layer
zip -r ../my-layer.zip python/
# Publish the layer
aws lambda publish-layer-version \
--layer-name common-deps \
--description "Shared Python dependencies" \
--zip-file fileb://my-layer.zip \
--compatible-runtimes python3.11 python3.12 \
--compatible-architectures arm64 x86_64
# Attach layer to a function
aws lambda update-function-configuration \
--function-name my-api-handler \
--layers "arn:aws:lambda:us-east-1:123456789012:layer:common-deps:1"
# List available layers
aws lambda list-layers --compatible-runtime python3.12# SQS trigger with batch processing
aws lambda create-event-source-mapping \
--function-name sqs-processor \
--event-source-arn arn:aws:sqs:us-east-1:123456789012:my-queue \
--batch-size 10 \
--maximum-batching-window-in-seconds 5 \
--function-response-types ReportBatchItemFailures
# DynamoDB Streams trigger
aws lambda create-event-source-mapping \
--function-name stream-processor \
--event-source-arn arn:aws:dynamodb:us-east-1:123456789012:table/my-table/stream/2026-01-01T00:00:00.000 \
--batch-size 100 \
--starting-position LATEST \
--maximum-retry-attempts 3 \
--bisect-batch-on-function-error \
--destination-config '{"OnFailure":{"Destination":"arn:aws:sqs:us-east-1:123456789012:dlq"}}'
# S3 event notification (via Lambda permission + S3 config)
aws lambda add-permission \
--function-name image-processor \
--statement-id s3-trigger \
--action lambda:InvokeFunction \
--principal s3.amazonaws.com \
--source-arn arn:aws:s3:::my-uploads-bucket \
--source-account 123456789012
aws s3api put-bucket-notification-configuration \
--bucket my-uploads-bucket \
--notification-configuration '{
"LambdaFunctionConfigurations": [{
"LambdaFunctionArn": "arn:aws:lambda:us-east-1:123456789012:function:image-processor",
"Events": ["s3:ObjectCreated:*"],
"Filter": {"Key": {"FilterRules": [{"Name": "suffix", "Value": ".jpg"}]}}
}]
}'
# Schedule with EventBridge (cron)
aws events put-rule \
--name daily-cleanup \
--schedule-expression "cron(0 2 * * ? *)" \
--state ENABLED
aws lambda add-permission \
--function-name daily-cleanup \
--statement-id eventbridge \
--action lambda:InvokeFunction \
--principal events.amazonaws.com \
--source-arn arn:aws:events:us-east-1:123456789012:rule/daily-cleanup
aws events put-targets \
--rule daily-cleanup \
--targets '[{"Id":"1","Arn":"arn:aws:lambda:us-east-1:123456789012:function:daily-cleanup"}]'# Create a function URL (public HTTPS endpoint)
aws lambda create-function-url-config \
--function-name my-api-handler \
--auth-type NONE \
--cors '{
"AllowOrigins": ["https://myapp.com"],
"AllowMethods": ["GET", "POST"],
"AllowHeaders": ["Content-Type"],
"MaxAge": 86400
}'
# Grant public invoke for function URL
aws lambda add-permission \
--function-name my-api-handler \
--statement-id function-url-public \
--action lambda:InvokeFunctionUrl \
--principal "*" \
--function-url-auth-type NONE# Enable provisioned concurrency to eliminate cold starts
aws lambda put-provisioned-concurrency-config \
--function-name my-api-handler \
--qualifier live \
--provisioned-concurrent-executions 10
# Set reserved concurrency (throttle limit)
aws lambda put-function-concurrency \
--function-name my-api-handler \
--reserved-concurrent-executions 100
# Enable SnapStart for Java functions (near-zero cold starts)
aws lambda update-function-configuration \
--function-name my-java-handler \
--snap-start '{"ApplyOn": "PublishedVersions"}'
aws lambda publish-version --function-name my-java-handlerCold start reduction tips:
arm64 architecture (Graviton) for faster init and lower cost# template.yaml - AWS SAM application
AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: My serverless API
Globals:
Function:
Runtime: python3.12
Architectures: [arm64]
MemorySize: 256
Timeout: 30
Tracing: Active
Environment:
Variables:
STAGE: !Ref Stage
LOG_LEVEL: INFO
Parameters:
Stage:
Type: String
Default: dev
AllowedValues: [dev, staging, prod]
Resources:
ApiFunction:
Type: AWS::Serverless::Function
Properties:
FunctionName: !Sub "${Stage}-api-handler"
Handler: app.handler
CodeUri: src/
Layers:
- !Ref DepsLayer
Events:
GetItems:
Type: Api
Properties:
Path: /items
Method: get
PostItem:
Type: Api
Properties:
Path: /items
Method: post
Policies:
- DynamoDBCrudPolicy:
TableName: !Ref ItemsTable
QueueProcessor:
Type: AWS::Serverless::Function
Properties:
FunctionName: !Sub "${Stage}-queue-processor"
Handler: sqs_processor.handler
CodeUri: src/
Events:
SQSEvent:
Type: SQS
Properties:
Queue: !GetAtt ProcessingQueue.Arn
BatchSize: 10
FunctionResponseTypes:
- ReportBatchItemFailures
DepsLayer:
Type: AWS::Serverless::LayerVersion
Properties:
LayerName: common-deps
ContentUri: layer/
CompatibleRuntimes:
- python3.12
ItemsTable:
Type: AWS::DynamoDB::Table
Properties:
TableName: !Sub "${Stage}-items"
BillingMode: PAY_PER_REQUEST
AttributeDefinitions:
- AttributeName: id
AttributeType: S
KeySchema:
- AttributeName: id
KeyType: HASH
ProcessingQueue:
Type: AWS::SQS::Queue
Properties:
QueueName: !Sub "${Stage}-processing"
VisibilityTimeout: 360
Outputs:
ApiEndpoint:
Value: !Sub "https://${ServerlessRestApi}.execute-api.${AWS::Region}.amazonaws.com/Prod"# SAM CLI commands
sam build
sam local invoke ApiFunction --event events/get-items.json
sam local start-api --port 3000
sam deploy --guided
sam logs --name ApiFunction --stack-name my-stack --tail| Problem | Cause | Fix |
|---|---|---|
| Function times out | Timeout too low or downstream slow | Increase timeout; check VPC/NAT config |
| Out of memory | Memory limit too small | Increase --memory-size; profile with CloudWatch Insights |
| Permission denied on AWS API | Execution role missing policy | Attach required policy to the execution role |
| Cold starts > 5s | Large package or VPC overhead | Use layers, arm64, provisioned concurrency; remove VPC if not needed |
| SQS messages reprocessed | Visibility timeout < function timeout | Set queue visibility timeout to 6x function timeout |
| Event source mapping disabled | Too many consecutive errors | Fix the function error; re-enable the mapping |
| Layer not found | Wrong region or deleted version | Verify layer ARN region matches function region |
| Canary deployment not shifting | Alias routing config wrong | Verify version numbers in routing config |
| Cannot invoke function URL | Missing resource-based policy | Add lambda:InvokeFunctionUrl permission |
aws-iam) - Execution roles and permissionsterraform-aws) - IaC deployment for Lambdaaws-s3) - S3 event triggersaws-vpc) - VPC configuration for Lambdaaws-cost-optimization) - Optimizing Lambda spend© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/aws-lambda of sickn33/agentic-awesome-skills.
Open the folder on GitHubat commit 1e53ce2
We found 6 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.
AWS Lambda next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AWS Lambda this skillsickn33/agentic-awesome-skills | 47k | 2 repos | ~3.3k | Automated safety check: Pass | MIT | |
| AWS Serverless Edazxkane/aws-skills | 367 | 4 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Polylith Base CreationDavidVujic/python-polylith | 553 | — | ~757 | Automated safety check: Pass | MIT | |
| Serverless IntegrationsDataDog/dd-trace-js | 836 | — | ~1.1k | Automated safety check: Pass | Custom licence | |
| Processing S3 Uploads With Step Functionsaws/agent-toolkit-for-aws | 2.8k | — | ~4k | Automated safety check: Pass | Apache-2.0 | |
| AWS Serverlessdavila7/claude-code-templates | 32k | 7 repos | ~2k | Automated safety check: Pass | MIT |
zxkane/aws-skills
AWS serverless and event-driven architecture expert based on Well-Architected Framework.
DavidVujic/python-polylith
Create a Polylith base with poly create base — the entry point of a deployable application (HTTP API, CLI, message-queue consumer, AWS Lambda handler, GCP Cloud Function, scheduled job).
DataDog/dd-trace-js
A skill your agent uses when adding, modifying, debugging, or reviewing dd-trace-js serverless platform integrations that create root invocation spans for AWS Lambda, Azure Functions, Google Cloud…
aws/agent-toolkit-for-aws
Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size.
davila7/claude-code-templates
Specialized skill for building production-ready serverless applications on AWS.
awslabs/agent-plugins
Build, run, debug, and operate applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments that run inside a container with up to 8-hour lifetimes.
sickn33/agentic-awesome-skills
Implements an interface in one of two named color modes, iridescent white or colorful black, from a parameterized starter that reports measured color intensity.
sickn33/agentic-awesome-skills
Saves a user's project decisions, rules and preferences into a project-local mdbase so later sessions and other agents can recover the intent.
sickn33/agentic-awesome-skills
Keeps project decisions, research and verified results available across coding-agent sessions through LWC memory, a document Wiki graph and a CodeGraph code index.
sickn33/agentic-awesome-skills
Guides an agent through assessing its own owner for cofounder fit, publishing an approved profile, and ranking complementary profiles other agents published for their owners.
sickn33/agentic-awesome-skills
Integracao com WhatsApp Business Cloud API (Meta). An agent skill from sickn33/agentic-awesome-skills.
sickn33/agentic-awesome-skills
Acts as a proxy for the Cline CLI, dispatching coding tasks one at a time, monitoring runs by hard evidence, relaying decisions to you and learning per-project preferences.
Works with
Categories
Build and deploy serverless functions on AWS Lambda. An agent skill from sickn33/agentic-awesome-skills. AWS Lambda is an agent skill from sickn33/agentic-awesome-skills. Build and deploy serverless functions on AWS Lambda.
AWS Lambda fits situations like: implementing serverless applications; tasks that involve Serverless; tasks that involve Performance optimization.
Run `npx skills add sickn33/agentic-awesome-skills --skill aws-lambda -a claude-code`. Or copy the skill folder (skills/aws-lambda in sickn33/agentic-awesome-skills) into .claude/skills/aws-lambda in your project. Claude Code loads it when a task matches its description.
Run `npx skills add sickn33/agentic-awesome-skills --skill aws-lambda -a codex`. Or copy the skill folder (skills/aws-lambda in sickn33/agentic-awesome-skills) into .agents/skills/aws-lambda in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill aws-lambda -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aws-lambda, .gemini/skills/aws-lambda, .github/skills/aws-lambda and .opencode/skills/aws-lambda in your project.
Going by SKILL.md and its folder, AWS Lambda needs the command-line tools its instructions call (aws and pip). Our summary lists: Python 3; Node.js. Compatibility (from SKILL.md): Requires the relevant OS/platform tooling and privileged access where noted. Docs-only; helper scripts and templates not bundled..
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
AWS Lambda is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with AWS Lambda: AWS Serverless Eda (zxkane/aws-skills, 367 stars), Polylith Base Creation (DavidVujic/python-polylith, 553 stars), Serverless Integrations (DataDog/dd-trace-js, 836 stars) and Processing S3 Uploads With Step Functions (aws/agent-toolkit-for-aws, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,304 GitHub stars. The repository holds 1,394 skills in this directory. The repository was last updated on October 6, 2026.
Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.