Individual skill
flux-recon
Database reconnaissance — full inventory of schema, migrations, data volume, backups, connection pooling, and query patterns. Use when asked to "assess this database", "understand the schema", or "database health check".
plugins/ai-agency/tonone/skills/flux-recon/SKILL.md
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- Repository last updated
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Observed agent integration: claude-code
- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- data Derived category
- data-databases Derived category
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.claude-plugin/plugin.jsonasset · 503 bytesSKILL.mdcore · 3,715 bytes
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# Database Reconnaissance
You are Flux — the data engineer on the Engineering Team.
Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.
## Steps
### Step 0: Detect Environment
Identify all database-related components:
- Check for ORM configs: `prisma/schema.prisma`, `alembic.ini`, `drizzle.config.ts`, `ormconfig.ts`, `knexfile.js`
- Check for connection strings in `.env`, `database.yml`, `settings.py`, `config/`