AI Integration

sql-splitter is optimized for AI-driven workflows.

llms.txt

sql-splitter includes an llms.txt file for AI agents:

https://sql-splitter.dev/llms.txt

This provides:

• Complete command reference
• Usage patterns
• Error handling guidance

AI agents can fetch this file to understand sql-splitter’s capabilities.

Agent Skills

sql-splitter provides an Agent Skill for coding assistants.

Install in Claude Code

git clone https://github.com/helgesverre/sql-splitter.git /tmp/sql-splitter
cp -r /tmp/sql-splitter/skills/sql-splitter ~/.claude/skills/

Install in Amp

amp skill add helgesverre/sql-splitter

Install in VS Code / GitHub Copilot

git clone https://github.com/helgesverre/sql-splitter.git /tmp/sql-splitter
cp -r /tmp/sql-splitter/skills/sql-splitter .github/skills/

Install in Cursor

git clone https://github.com/helgesverre/sql-splitter.git /tmp/sql-splitter
cp -r /tmp/sql-splitter/skills/sql-splitter .cursor/skills/

JSON Output for Agents

All commands support --json for machine-readable output:

sql-splitter analyze dump.sql --json

Agents can parse this structured output programmatically.

Automation-Friendly Design

sql-splitter is designed for automation:

• Consistent exit codes: 0 success, 1 error, 2 bad args
• JSON output: Machine-readable for every command
• Glob patterns: Process multiple files at once
• --dry-run: Safe exploration
• --fail-fast: Stop on first error
• Streaming I/O: Composable with Unix tools

Example Agent Prompts

”Validate my SQL dumps"

Agent: I'll check your SQL dumps for issues.

sql-splitter validate "dumps/*.sql" --strict --json

Result: Found 3 issues in backup_2024.sql:
- Line 42: Syntax error near 'CREAT'
- Duplicate PK in users table
- FK violation: orders.user_id references non-existent user

"Convert MySQL to PostgreSQL"

Agent: I'll convert your MySQL dump to PostgreSQL.

sql-splitter validate mysql_dump.sql --strict
sql-splitter convert mysql_dump.sql --to postgres -o postgres_dump.sql --progress
sql-splitter validate postgres_dump.sql --dialect postgres --strict

Result: Conversion complete. 2 warnings about ENUM types
that were converted to VARCHAR with CHECK constraints.

"Create a safe dev dataset”

Agent: I'll create an anonymized sample for development.

sql-splitter sample prod.sql --percent 10 --preserve-relations -o - | \
  sql-splitter redact - --hash "*.email" --fake "*.name" --null "*.ssn" -o dev.sql

sql-splitter validate dev.sql --strict

Result: Created dev.sql with 10% of data, all PII anonymized.

Best Practices for Agents

1. Always validate before and after operations
2. Use --json for parsing results
3. Use --dry-run for exploration
4. Use --progress for user feedback
5. Handle warnings - check JSON for warning arrays