db-query

---

name: db-query description: Execute read-only queries against databases in any environment. Use when asked about "SQL", "check data", "count records", "find rows", "query database", "how many X?", "look up Y". SKIP: running migrations (use db-migrate); service health (use service-status). allowed-tools: Bash Read AskUserQuestion argument-hint: "[query description] [environment]" model: haiku

Step 0 — Load configuration

Check if /tmp/ops-suite-session/config.json exists:

• If yes, read it (pre-parsed by session-start hook).
• If no, read ${XDG_CONFIG_HOME:-$HOME/.config}/ops-suite/config.yaml (preferred) or the plugin's config.yaml (legacy), parse it, and write to /tmp/ops-suite-session/config.json for other skills to reuse. If neither exists, tell the user to run /ops-suite:configure (or copy config.example.yaml to ~/.config/ops-suite/config.yaml and fill in their values). Stop here.

Extract:

• database — determines which adapter to load (postgresql, mysql, mongodb)
• orchestrator — for port-forward commands
• environments — connection details
• deploy.local_ports — local ports for database connections

Also read the reference at references/query-examples.md (in this skill's directory) for common query patterns.

Step 1 — Load adapter

Read the adapter file at adapters/{database}.md (in this skill's directory). If the adapter does not exist, tell the user that the database {database} is not yet supported and stop.

Step 2 — Determine target environment

If $ARGUMENTS contains an environment name, use it. Otherwise ask the user.

Step 3 — Establish database connection

Check if a port-forward is already active on the expected local port (deploy.local_ports.{env_name}).

If not active:

1. Start a port-forward using the orchestrator:

   kubectl --context={env.context} port-forward svc/{env.services.database.name} {deploy.local_ports.{env_name}}:{env.services.database.port} -n {env.services.database.namespace || env.namespaces.infra} &
   

2. Verify the connection is working

Retrieve or ask for credentials. Never hardcode credentials.

Step 4 — Formulate query

If $ARGUMENTS contains a natural language description:

• Translate it into a SQL query (or equivalent for the database type)
• Show the query to the user and ask for confirmation before running

If $ARGUMENTS contains raw SQL:

• Use it directly, but validate it first

Constraints:

• Default to read-only queries (SELECT, EXPLAIN)
• If the user requests a write operation (INSERT, UPDATE, DELETE), warn them and ask for explicit confirmation
• Always use LIMIT to prevent unbounded result sets (default LIMIT 50)
• Wrap queries in a transaction with ROLLBACK for safety when testing writes

Step 5 — Execute query

Use the adapter's query execution command. The script at scripts/query.js (in this skill's directory) can be used as a helper for PostgreSQL.

Step 6 — Format and present results

Present results in a clear, readable format:

Environment: {env_name}
Database:    {database_name}
Query:       {sql_query}
Rows:        {row_count}

Results:
| column_1 | column_2 | column_3 |
|----------|----------|----------|
| value    | value    | value    |

Query time: {duration}ms

If results are too many to display, show the first 20 rows and provide the total count.

Step 7 — Cleanup

If a port-forward was started in this session, provide the cleanup command but do not kill it automatically (the user may want to run more queries).

Important notes

• Always use parameterized queries when possible to prevent SQL injection
• Be aware of PgBouncer limitations: avoid multi-statement queries, SET commands, or prepared statements when connecting through PgBouncer
• For large datasets, suggest using EXPLAIN ANALYZE first to estimate query cost