altimate-code: Skill for OpenCode

Data Parity (Table Diff)

CRITICAL: Regulated / Sensitive Data

data_diff includes up to 5 sample diff rows in the tool output so you can see which values differ. Those rows are part of the conversation and are sent to the LLM provider you're using.

Before running data_diff against a table that might contain PII, PHI, PCI, or other regulated data:

1. Ask the user whether the target contains regulated columns.
2. If yes, prefer algorithm: "profile" — it compares column-level statistics (count, nulls, min/max, distinct count) without any row values leaving the database.
3. If a row-level diff is genuinely required, tell the user that up to 5 sample rows will be sent to the LLM and get explicit approval before calling the tool.
4. Consider scoping with where_clause to exclude sensitive customers/accounts first.

Default to profile mode whenever the table name suggests regulated data (customers, patients, orders, payments, accounts, users, etc.) unless the user explicitly requests row-level comparison.

CRITICAL: Always Start With a Plan

Before doing anything else, generate a numbered TODO list for the user:

Here's my plan:
1. [ ] List available warehouse connections
2. [ ] Inspect schema, discover primary key candidates, and detect auto-timestamp columns
3. [ ] Confirm primary keys with you
4. [ ] Confirm which auto-timestamp columns to exclude
5. [ ] Check row counts on both sides
6. [ ] Run column-level profile (cheap — no row scan)
7. [ ] Ask whether to proceed with row-level diff (may be expensive for large tables)
8. [ ] Run targeted row-level diff on diverging columns only
9. [ ] Present findings with scope, filters, time period, columns compared/excluded, and assumptions

Update each item to [x] as you complete it. This plan should be visible before any tool is called.

CRITICAL: Use data_diff Tool — Never Write Manual Diff SQL

NEVER write SQL to diff tables manually (e.g., EXCEPT, FULL OUTER JOIN, MINUS). ALWAYS use the data_diff tool for any comparison operation.