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Rds

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itsmostafa
rds

AWS RDS relational database service for managed databases. Use when provisioning databases, configuring backups, managing replicas, troubleshooting connectivity, or optimizing performance.

Overview

Publisheritsmostafa
Repositoryaws-agent-skills
Skill namerds
Stars
1.2K
Forks
445
Bundled files
1
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.

  • 1 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 Rds 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/rds
  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/rds .claude/skills/rds
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rds 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 Rds 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 Rds 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 RDS

Amazon Relational Database Service (RDS) provides managed relational databases including MySQL, PostgreSQL, MariaDB, Oracle, SQL Server, and Aurora. RDS handles provisioning, patching, backups, and failover.

Table of Contents

Core Concepts

DB Instance Classes

CategoryExampleUse Case
Standarddb.m6g.largeGeneral purpose
Memory Optimizeddb.r6g.largeHigh memory workloads
Burstabledb.t3.mediumVariable workloads, dev/test

Storage Types

TypeIOPSUse Case
gp33,000-16,000Most workloads
io1/io2Up to 256,000High-performance OLTP
magneticN/ALegacy, avoid

Multi-AZ Deployments

  • Multi-AZ Instance: Synchronous standby in different AZ
  • Multi-AZ Cluster: One writer, two reader instances (Aurora-like)

Read Replicas

Asynchronous copies for read scaling. Can be cross-region.

Common Patterns

Create a PostgreSQL Instance

AWS CLI:

bash
# Create DB subnet group
aws rds create-db-subnet-group \
  --db-subnet-group-name my-db-subnet-group \
  --db-subnet-group-description "Private subnets for RDS" \
  --subnet-ids subnet-12345678 subnet-87654321

# Create security group (allow PostgreSQL from app)
aws ec2 create-security-group \
  --group-name rds-postgres-sg \
  --description "RDS PostgreSQL access" \
  --vpc-id vpc-12345678

aws ec2 authorize-security-group-ingress \
  --group-id sg-rds12345 \
  --protocol tcp \
  --port 5432 \
  --source-group sg-app12345

# Create RDS instance
aws rds create-db-instance \
  --db-instance-identifier my-postgres \
  --db-instance-class db.t3.medium \
  --engine postgres \
  --engine-version 16.1 \
  --master-username admin \
  --master-user-password 'SecurePassword123!' \
  --allocated-storage 100 \
  --storage-type gp3 \
  --db-subnet-group-name my-db-subnet-group \
  --vpc-security-group-ids sg-rds12345 \
  --multi-az \
  --backup-retention-period 7 \
  --storage-encrypted \
  --no-publicly-accessible

boto3:

python
import boto3

rds = boto3.client('rds')

response = rds.create_db_instance(
    DBInstanceIdentifier='my-postgres',
    DBInstanceClass='db.t3.medium',
    Engine='postgres',
    EngineVersion='16.1',
    MasterUsername='admin',
    MasterUserPassword='SecurePassword123!',
    AllocatedStorage=100,
    StorageType='gp3',
    DBSubnetGroupName='my-db-subnet-group',
    VpcSecurityGroupIds=['sg-rds12345'],
    MultiAZ=True,
    BackupRetentionPeriod=7,
    StorageEncrypted=True,
    PubliclyAccessible=False
)

Create Read Replica

bash
aws rds create-db-instance-read-replica \
  --db-instance-identifier my-postgres-replica \
  --source-db-instance-identifier my-postgres \
  --db-instance-class db.t3.medium \
  --availability-zone us-east-1b

Take a Snapshot

bash
aws rds create-db-snapshot \
  --db-snapshot-identifier my-postgres-snapshot-2024-01-15 \
  --db-instance-identifier my-postgres

Restore from Snapshot

bash
aws rds restore-db-instance-from-db-snapshot \
  --db-instance-identifier my-postgres-restored \
  --db-snapshot-identifier my-postgres-snapshot-2024-01-15 \
  --db-instance-class db.t3.medium \
  --db-subnet-group-name my-db-subnet-group \
  --vpc-security-group-ids sg-rds12345

Point-in-Time Recovery

bash
aws rds restore-db-instance-to-point-in-time \
  --source-db-instance-identifier my-postgres \
  --target-db-instance-identifier my-postgres-pitr \
  --restore-time 2024-01-15T10:30:00Z \
  --db-instance-class db.t3.medium

Modify Instance

bash
# Change instance class (with downtime)
aws rds modify-db-instance \
  --db-instance-identifier my-postgres \
  --db-instance-class db.m6g.large \
  --apply-immediately

# Scale storage (no downtime)
aws rds modify-db-instance \
  --db-instance-identifier my-postgres \
  --allocated-storage 200 \
  --apply-immediately

Connect with IAM Authentication

python
import boto3
import psycopg2

rds = boto3.client('rds')

# Generate auth token
token = rds.generate_db_auth_token(
    DBHostname='my-postgres.abc123.us-east-1.rds.amazonaws.com',
    Port=5432,
    DBUsername='iam_user',
    Region='us-east-1'
)

# Connect
conn = psycopg2.connect(
    host='my-postgres.abc123.us-east-1.rds.amazonaws.com',
    port=5432,
    database='mydb',
    user='iam_user',
    password=token,
    sslmode='require'
)

CLI Reference

Instance Management

CommandDescription
aws rds create-db-instanceCreate instance
aws rds describe-db-instancesList instances
aws rds modify-db-instanceModify settings
aws rds delete-db-instanceDelete instance
aws rds reboot-db-instanceReboot instance
aws rds start-db-instanceStart stopped instance
aws rds stop-db-instanceStop instance

Backups

CommandDescription
aws rds create-db-snapshotManual snapshot
aws rds describe-db-snapshotsList snapshots
aws rds restore-db-instance-from-db-snapshotRestore from snapshot
aws rds restore-db-instance-to-point-in-timePoint-in-time restore
aws rds copy-db-snapshotCopy snapshot

Replicas

CommandDescription
aws rds create-db-instance-read-replicaCreate read replica
aws rds promote-read-replicaPromote to standalone

Best Practices

Security

  • Never make publicly accessible — use VPC and security groups
  • Enable encryption at rest (KMS) and in transit (SSL)
  • Use IAM authentication for application access
  • Store credentials in Secrets Manager with rotation
  • Use parameter groups to enforce SSL
bash
# Enforce SSL in PostgreSQL
aws rds modify-db-parameter-group \
  --db-parameter-group-name my-pg-params \
  --parameters "ParameterName=rds.force_ssl,ParameterValue=1,ApplyMethod=pending-reboot"

Performance

  • Right-size instances — monitor CPU, memory, IOPS
  • Use gp3 for cost-effective performance
  • Enable Performance Insights for query analysis
  • Use read replicas for read scaling
  • Optimize queries — check slow query log

High Availability

  • Enable Multi-AZ for production
  • Use Aurora for mission-critical workloads
  • Configure appropriate backup retention
  • Test failover periodically
  • Monitor replication lag for replicas

Cost Optimization

  • Use Reserved Instances for steady-state workloads
  • Stop dev/test instances when not in use
  • Delete old snapshots regularly
  • Right-size instance classes

Troubleshooting

Cannot Connect

Causes:

  1. Security group not allowing access
  2. Instance not in VPC subnet
  3. SSL required but not used
  4. Wrong endpoint/port

Debug:

bash
# Check security group
aws ec2 describe-security-groups --group-ids sg-rds12345

# Check instance status
aws rds describe-db-instances \
  --db-instance-identifier my-postgres \
  --query "DBInstances[0].{Status:DBInstanceStatus,Endpoint:Endpoint}"

# Test connectivity from EC2
nc -zv my-postgres.abc123.us-east-1.rds.amazonaws.com 5432

High CPU/Memory

Debug:

bash
# Enable Enhanced Monitoring
aws rds modify-db-instance \
  --db-instance-identifier my-postgres \
  --monitoring-interval 60 \
  --monitoring-role-arn arn:aws:iam::123456789012:role/rds-monitoring-role

# Enable Performance Insights
aws rds modify-db-instance \
  --db-instance-identifier my-postgres \
  --enable-performance-insights \
  --performance-insights-retention-period 7

Solutions:

  • Scale up instance class
  • Optimize slow queries
  • Add read replicas
  • Check for locking/blocking

Storage Full

Symptom: Instance becomes unavailable

Prevention:

bash
# Enable storage autoscaling
aws rds modify-db-instance \
  --db-instance-identifier my-postgres \
  --max-allocated-storage 500

# Set CloudWatch alarm
aws cloudwatch put-metric-alarm \
  --alarm-name "RDS-Storage-Low" \
  --metric-name FreeStorageSpace \
  --namespace AWS/RDS \
  --dimensions Name=DBInstanceIdentifier,Value=my-postgres \
  --statistic Average \
  --period 300 \
  --threshold 10000000000 \
  --comparison-operator LessThanThreshold \
  --evaluation-periods 2 \
  --alarm-actions arn:aws:sns:us-east-1:123456789012:alerts

Replication Lag

Monitor:

bash
aws cloudwatch get-metric-statistics \
  --namespace AWS/RDS \
  --metric-name ReplicaLag \
  --dimensions Name=DBInstanceIdentifier,Value=my-postgres-replica \
  --start-time $(date -d '1 hour ago' -u +%Y-%m-%dT%H:%M:%SZ) \
  --end-time $(date -u +%Y-%m-%dT%H:%M:%SZ) \
  --period 60 \
  --statistics Average

Causes:

  • Replica instance too small
  • Heavy write load
  • Network issues
  • Long-running queries on replica

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 Rds AI skill do?

AWS RDS relational database service for managed databases. Use when provisioning databases, configuring backups, managing replicas, troubleshooting connectivity, or optimizing performance.

Why use Rds on TypingMind?

Because you install it once and use it with any model. Rds 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 Rds in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/itsmostafa/aws-agent-skills/tree/main/skills/rds. 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 Rds?

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 Rds?

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

Is the Rds 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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