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Database Backup

Community
seb1n
database-backup

Create, schedule, and verify database backups with support for full, incremental, and point-in-time recovery strategies. Use when the user requests database backup or provides relevant inputs for this workflow.

Overview

Publisherseb1n
Repositoryawesome-ai-agent-skills
Skill namedatabase-backup
Stars
188
Forks
35
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by seb1n on GitHub. Read the source before you install it.

Installation

Install the Database Backup 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.
  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/seb1n/awesome-ai-agent-skills.git /tmp/awesome-ai-agent-skills
mkdir -p .claude/skills
cp -r /tmp/awesome-ai-agent-skills/database/database-backup .claude/skills/database-backup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Database Backup 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 Database Backup 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 Database Backup 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.

Database Backup

This skill enables an AI agent to plan and execute database backup strategies across PostgreSQL, MySQL, and MongoDB. The agent selects the appropriate backup type (full, incremental, differential, or point-in-time), generates backup scripts with compression and encryption, configures automated scheduling via cron or similar tools, defines retention policies, and verifies backup integrity through restore tests.

Workflow

  1. Assess backup requirements: Determine the database type, size, acceptable data loss window (Recovery Point Objective), and acceptable downtime (Recovery Time Objective). Identify whether the backup must be consistent (application-level locks or snapshots) and whether the database can tolerate brief locking during the backup.

  2. Select backup strategy: Choose the appropriate backup type based on requirements. Full backups capture the entire database and are simplest to restore but slowest to create. Incremental backups capture only changes since the last backup, saving time and storage. Differential backups capture changes since the last full backup, offering a middle ground. Point-in-time recovery (PITR) uses write-ahead logs or oplogs to restore to any moment, providing the lowest RPO.

  3. Generate backup scripts: Produce shell scripts that invoke the correct backup tool for the target database. Include compression (gzip, lz4, or zstd), optional encryption (GPG or OpenSSL), timestamped filenames, and error handling with exit codes. Script should log output for monitoring.

  4. Configure scheduling and retention: Set up automated execution using cron, systemd timers, or a task scheduler. Define a retention policy (e.g., keep 7 daily, 4 weekly, 12 monthly backups) and implement cleanup of expired backups to manage storage usage.

  5. Verify backup integrity: After each backup, verify the file is non-empty and checksums are valid. Periodically perform a test restore to a staging environment to confirm the backup is actually recoverable. Alert on verification failures.

  6. Document and monitor: Record the backup schedule, retention policy, storage location, and restore procedure. Set up monitoring alerts for missed backups or backup failures using tools like Prometheus, Datadog, or simple email notifications.

Supported Technologies

  • PostgreSQL: pg_dump, pg_basebackup, WAL archiving for PITR
  • MySQL: mysqldump, mysqlpump, Percona XtraBackup, binlog for PITR
  • MongoDB: mongodump, mongorestore, filesystem snapshots, oplog for PITR
  • Compression: gzip, lz4, zstd, pigz
  • Encryption: GPG, OpenSSL AES-256
  • Storage: Local disk, AWS S3, Google Cloud Storage, Azure Blob Storage

Usage

Provide the agent with your database type, name, and connection details. Specify your RPO/RTO requirements, preferred storage destination, and whether you need encryption. The agent will generate a complete backup solution including scripts, scheduling, retention policy, and verification steps.

Examples

Example 1: PostgreSQL Full Backup with Cron Schedule

Request: Set up a nightly full backup of a PostgreSQL database with 30-day retention, compressed and uploaded to a local backup directory.

bash
#!/usr/bin/env bash
# pg_backup.sh — Nightly PostgreSQL full backup
set -euo pipefail

DB_NAME="production"
DB_USER="backup_user"
BACKUP_DIR="/var/backups/postgresql"
RETENTION_DAYS=30
TIMESTAMP=$(date +%Y%m%d_%H%M%S)
BACKUP_FILE="${BACKUP_DIR}/${DB_NAME}_${TIMESTAMP}.sql.gz"

mkdir -p "$BACKUP_DIR"

echo "[$(date)] Starting backup of database '${DB_NAME}'..."
pg_dump -U "$DB_USER" -h localhost -Fc "$DB_NAME" | gzip > "$BACKUP_FILE"

# Verify the backup file is non-empty
if [ ! -s "$BACKUP_FILE" ]; then
    echo "[$(date)] ERROR: Backup file is empty. Aborting." >&2
    exit 1
fi

FILE_SIZE=$(du -h "$BACKUP_FILE" | cut -f1)
echo "[$(date)] Backup complete: ${BACKUP_FILE} (${FILE_SIZE})"

# Clean up backups older than retention period
find "$BACKUP_DIR" -name "${DB_NAME}_*.sql.gz" -mtime +${RETENTION_DAYS} -delete
echo "[$(date)] Expired backups removed (older than ${RETENTION_DAYS} days)."

Cron entry (runs daily at 2:00 AM):

0 2 * * * /usr/local/bin/pg_backup.sh >> /var/log/pg_backup.log 2>&1

Example 2: MongoDB Backup and Restore Procedure

Request: Back up a MongoDB replica set and document the restore procedure.

Backup script:

bash
#!/usr/bin/env bash
# mongo_backup.sh — MongoDB replica set backup
set -euo pipefail

: "${MONGO_URI:?Set MONGO_URI through the secret manager or environment}"
BACKUP_DIR="/var/backups/mongodb"
TIMESTAMP=$(date +%Y%m%d_%H%M%S)
DUMP_DIR="${BACKUP_DIR}/dump_${TIMESTAMP}"

mkdir -p "$BACKUP_DIR"

echo "[$(date)] Starting mongodump..."
mongodump --uri="$MONGO_URI" --oplog --out="$DUMP_DIR"

# Compress the dump directory
tar -czf "${DUMP_DIR}.tar.gz" -C "$BACKUP_DIR" "dump_${TIMESTAMP}"
tar -tzf "${DUMP_DIR}.tar.gz" >/dev/null

# Refuse cleanup unless the resolved path is the expected timestamped child.
case "$DUMP_DIR" in
  "$BACKUP_DIR"/dump_[0-9]*) rm -rf -- "$DUMP_DIR" ;;
  *) echo "Refusing unsafe cleanup path: $DUMP_DIR" >&2; exit 1 ;;
esac

echo "[$(date)] Backup complete: ${DUMP_DIR}.tar.gz"

# Retain only the last 14 backups
ls -t ${BACKUP_DIR}/dump_*.tar.gz | tail -n +15 | xargs -r rm --

Restore procedure:

bash
# 1. Extract the backup archive
tar -xzf /var/backups/mongodb/dump_20250115_020000.tar.gz -C /tmp/

# 2. Restore to the target MongoDB instance
: "${RESTORE_MONGO_URI:?Set RESTORE_MONGO_URI through the secret manager or environment}"
: "${RESTORE_TARGET_CONFIRMED:?Set RESTORE_TARGET_CONFIRMED=yes only after verifying the target is the authorized restore environment}"
[ "$RESTORE_TARGET_CONFIRMED" = "yes" ] || { echo "Restore target is not confirmed" >&2; exit 1; }
mongorestore --uri="$RESTORE_MONGO_URI" \
  --oplogReplay --drop /tmp/dump_20250115_020000/

# 3. Verify collections and document counts
mongosh --eval "db.adminCommand({listDatabases: 1})"

Best Practices

  • Test restores regularly — a backup you have never restored is a backup you cannot trust. Schedule monthly restore drills to a staging environment.
  • Encrypt backups at rest and in transit using GPG or AES-256, especially when storing offsite or in cloud storage. Never store encryption keys alongside the backups.
  • Use the --oplog flag (MongoDB) or WAL archiving (PostgreSQL) to enable point-in-time recovery, which dramatically reduces potential data loss.
  • Store backups in a separate failure domain — a different server, availability zone, or cloud region — so a single infrastructure failure does not destroy both the database and its backups.
  • Monitor backup jobs with alerts — silence is not success. Alert on missing backups, zero-byte files, or checksums that do not match.
  • Document the full restore procedure with exact commands, expected timings, and who is responsible, so recovery can happen under pressure without guesswork.

Safety and Permissions

  • Start with configuration inspection and a restore plan. Do not install schedules, delete expired backups, upload data, or start a restore without explicit authorization for the named environment.
  • Treat restore commands such as --drop as destructive. Resolve and independently verify the destination, confirm it is the intended isolated restore target, capture a pre-restore recovery point where applicable, and stop if identity is ambiguous.
  • Keep credentials out of scripts, command output, logs, and generated examples. Prefer secret-manager injection or protected client configuration with least-privilege backup and restore identities.
  • Preserve the source backup and its checksum throughout a restore drill. Never report recoverability from archive listing or checksum verification alone; validate a representative restore and application-level invariants.

Edge Cases

  • Large databases exceeding disk space: For databases larger than available local storage, stream backups directly to object storage (e.g., pg_dump | gzip | aws s3 cp - s3://bucket/backup.gz) to avoid local disk exhaustion.
  • Active write traffic during backup: Use pg_dump with --snapshot or MongoDB's --oplog to get a consistent point-in-time backup even while writes continue. For MySQL, use Percona XtraBackup for hot backups of InnoDB without locking.
  • Backup of encrypted databases: If Transparent Data Encryption (TDE) is enabled, ensure the encryption keys are backed up separately and that the backup process captures encrypted data in a restorable format.
  • Cross-region replication lag: When backing up from a replica, verify replication lag is zero or near-zero before starting the backup to avoid capturing stale data.
  • Backup credential rotation: Store credentials in a secrets manager (Vault, AWS Secrets Manager) rather than hardcoding them in scripts, and ensure backup scripts can handle credential rotation without manual updates.

Frequently asked questions

What does the Database Backup AI skill do?

Create, schedule, and verify database backups with support for full, incremental, and point-in-time recovery strategies. Use when the user requests database backup or provides relevant inputs for this workflow.

Why use Database Backup on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/seb1n/awesome-ai-agent-skills/tree/main/database/database-backup. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Database Backup?

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 Database Backup?

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

Is the Database Backup AI skill free?

Yes. It is published on GitHub by seb1n 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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