mcpbeat Sign in

AWS CLI Beast Agent Skill

Provides advanced AWS CLI patterns for managing EC2, Lambda, S3, DynamoDB, RDS, VPC, IAM, and CloudWatch. Generates bulk operation scripts, automates cross-service workflows, validates security configurations, and executes JMESPath queries for complex filtering. Triggers on "aws cli help", "aws command line", "aws scripting", "aws automation", "aws batch operations", "aws bulk operations", "aws cli pagination", "aws multi-region", "aws profiles", "aws cli troubleshooting".

15k tokens
context cost
the whole folder, loaded on every use
7
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
316
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill aws-cli-beast

The instruction itself

20 sections, as written by the author

AWS CLI Beast Mode

Overview

Advanced AWS CLI patterns for speed, precision, and security-first automation. Covers JMESPath queries, bulk operations, waiters, cross-account access, and destructive operation safety.

When to Use

  • Bulk operations across thousands of AWS resources
  • Advanced JMESPath filtering and output transformation
  • Automated scripts for AWS routines
  • Multi-profile and multi-region management
  • Security auditing and compliance checks
  • CLI-driven infrastructure-as-code workflows

Instructions

Step 1: Categorize the Request

| Category | Services | Commands |

|----------|----------|----------|

| Compute | EC2, Lambda | describe-instances, invoke, publish-version |

| Storage | S3 | sync, cp, mb, rb, presign |

| Database | DynamoDB, RDS | query, scan, batch-write-item |

| Networking | VPC, Route53 | describe-vpcs, describe-security-groups |

| Security | IAM | simulate-principal-policy, get-policy-version |

| Observability | CloudWatch | get-metric-statistics, filter-log-events |

Step 2: Apply Beast Mode Principles

  • Dry-run first: Always validate with --dryrun or --dry-run
  • Query server-side: Use --query with JMESPath to filter before transfer
  • Batch intelligently: Paginate with --max-results and parallelize with xargs
  • Wait properly: Use built-in waiters or exponential backoff polling
  • Switch contexts: Use --profile and --region for multi-account operations

Step 3: Validate Destructive Operations

MANDATORY for any destructive operation:

# S3 sync with delete - MUST dry-run first
aws s3 sync s3://source/ s3://dest/ --delete --dryrun
# Review output, then remove --dryrun only if satisfied

# Bulk EC2 stop - validate targets first
aws ec2 describe-instances \
  --filters "Name=tag:Environment,Values=development" \
  --query 'Reservations[].Instances[?State.Name==`running`].InstanceId' \
  --output text
# Confirm list, then pipe to stop command

# IAM policy attachment - simulate first
aws iam simulate-principal-policy \
  --policy-source-arn arn:aws:iam::123456789012:user/myuser \
  --action-names s3:DeleteObject \
  --resource-arns arn:aws:s3:::my-bucket/*

Step 4: Reference Detailed Guides

  • compute-mastery.md - EC2, Lambda, Spot Fleets, ASG
  • data-ops-beast.md - S3 multipart, DynamoDB batch, RDS snapshots
  • networking-security-hardened.md - VPC Flow Logs, IAM policies, security groups
  • automation-patterns.md - Shell aliases, JMESPath templates, CI/CD integration

Examples

Example 1: Bulk EC2 Stop

"Stop all development instances"

# 1. Dry-run: identify targets
aws ec2 describe-instances \
  --filters "Name=tag:Environment,Values=development" \
           "Name=instance-state-name,Values=running" \
  --query 'Reservations[].Instances[].InstanceId' \
  --output text

# 2. Confirm IDs, then execute
aws ec2 describe-instances \
  --filters "Name=tag:Environment,Values=development" \
           "Name=instance-state-name,Values=running" \
  --query 'Reservations[].Instances[].InstanceId' \
  --output text | xargs aws ec2 stop-instances --instance-ids

Example 2: S3 Migration with Encryption

"Migrate data between buckets with SSE"

# 1. Dry-run migration
aws s3 sync s3://source-bucket/ s3://dest-bucket/ \
  --sse AES256 \
  --storage-class GLACIER \
  --exclude "*.tmp" \
  --dryrun

# 2. Enable versioning on destination
aws s3api put-bucket-versioning \
  --bucket dest-bucket \
  --versioning-configuration Status=Enabled

# 3. Execute after review
aws s3 sync s3://source-bucket/ s3://dest-bucket/ \
  --sse AES256 \
  --storage-class GLACIER \
  --exclude "*.tmp"

Example 3: IAM Security Audit

"Find overprivileged IAM users"

aws iam list-users --query 'Users[].UserName' --output text | \
while read user; do
  echo "Checking $user..."
  aws iam simulate-principal-policy \
    --policy-source-arn "arn:aws:iam::123456789012:user/$user" \
    --action-names DeleteItem,DeleteTable,DeleteFunction \
    --resource-arns "*" \
    --query 'EvaluationResults[?EvalDecision==`allowed`]'
done

Example 4: Multi-Region Lambda Deployment

"Deploy Lambda to all regions"

for region in us-east-1 us-west-2 eu-west-1; do
  echo "Deploying to $region..."
  aws lambda update-function-code \
    --function-name my-function \
    --zip-file fileb://function.zip \
    --region $region \
    --publish
  aws lambda wait function-active \
    --function-name my-function \
    --region $region
done

Example 5: JMESPath Advanced Filtering

"Get running instances with specific tags as table"

aws ec2 describe-instances \
  --query 'Reservations[].Instances[?State.Name==`running`].[InstanceId,Tags[?Key==`Name`].Value[0]|[0],PrivateIpAddress]' \
  --output table

Best Practices

  • Use --output json for programmatic processing
  • Filter with JMESPath server-side before transfer
  • Implement retry logic with exponential backoff
  • Use waiters instead of manual polling loops
  • Tag all resources for cost allocation and automation
  • Separate dev/staging/prod with AWS profiles
  • Enable CloudTrail for audit compliance
  • Validate IAM policies with simulate-principal-policy before attachment
  • Use --dry-run on every state-modifying operation

10. Enable MFA for security-sensitive operations

Constraints and Warnings

Rate Limiting

  • AWS API throttling applies; use --max-throttle and exponential backoff
  • Check aws service-quotas for current limits

Pagination

  • Default page size is variable; use --max-results for consistency
  • Use --no-paginate with jq for full dataset processing

Destructive Operations

  • S3 sync --delete: Irreversibly removes files not in source
  • EC2 terminate-instances: Cannot be undone; validate instance IDs first
  • IAM detach/policy: May break existing access; simulate before applying
  • RDS delete-db-instance: Snapshots do not protect all scenarios; verify retention

Security

  • Never commit AWS credentials; use aws configure or environment variables
  • Rotate access keys regularly with aws iam create-access-key
  • Use least-privilege: simulate before granting permissions

Other skills for the same job

different authors, same section of the catalogue
Azure Kubernetes Automatic Readiness
by microsoft
vendor ×3

Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.

13k tokens
Capacity
by microsoft
vendor ×3

Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

6k tokens scripts
Customize
by microsoft
vendor ×3

Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).

8k tokens
Deploy Model
by microsoft
vendor ×3

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).

26k tokens scripts
Preset
by microsoft
vendor ×3

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

9k tokens
Lamindb
by christophacham
×3

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

22k tokens
Latchbio Integration
by christophacham
×3

Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.

12k tokens
Modal
by christophacham
×3

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

17k tokens

How to use it

Copy the folder

Take giuseppe-trisciuoglio/aws-cli-beast from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.