datus-ai/datus-agent/transfer-reconciliation

Transfer Reconciliation

Use this skill at the end of a transfer_query_result run. It is intentionally lightweight: the built-in layer already compares tool-reported source and target row counts, so this skill only demonstrates a small target-side sanity check. Project-specific or strict source-vs-target checks should live in a project/user validator skill.

When this skill fires

ValidationHook triggers this skill automatically at the end of any gen_job agent run that produced one or more TransferTarget deliverables. When the run stayed intra-database (no transfer_query_result calls), this skill is not invoked.

You never call this skill directly. The hook starts a read-only sub-agent whose only job is to execute the checks below against the run's transfer targets and emit a structured JSON report.

What you receive

The hook hands you a SessionTarget containing one or more TransferTarget records. Each record carries only:

• source.name — the source connector key (route execute_sql here for

source-side probes only when a project-specific validator explicitly needs them).

• target.datasource / target.database / target.db_schema /

target.table — the target coordinates.

• source_row_count, transferred_row_count — tool-reported counts

(authoritative for check 1).

Default validator behavior must avoid expensive source re-scans. Do not infer or search for the original source table; many transfers are derived queries, joins, or aggregations. Treat source_row_count / transferred_row_count as the source-side evidence.

Core workflow

For every TransferTarget in the session, run only these example checks:

1. Row count parity — report whether tool-reported source_row_count and

transferred_row_count match. This should normally already be present in the precheck context from the built-in layer; summarize it instead of querying the source.

1. Target row count — run one target-side COUNT(*) query using

TransferTarget.target.datasource and the target table coordinate. Compare it with transferred_row_count.

1. Target sample — optionally read up to 5 target rows to confirm the table

is queryable. This is advisory and should not become blocking unless the target query itself fails.

Stop after these checks. Do not run null-ratio, min/max, distinct-count, duplicate-key, sample-diff, or numeric-aggregate checks in the built-in skill. Those are examples for user-defined strict validators.

Tools

You have read-only access to: list_databases, list_schemas, list_tables, describe_table, search_table, execute_sql. Any write tool is explicitly excluded.

Critical rules

• execute_sql takes a datasource=<connector key> kwarg — it must be the

concrete connector key from the TransferTarget, not the literal words "source" or "target". Read it from the target payload:

• For source-side queries: use the value of TransferTarget.source.name

(e.g. datasource="pg_prod").

• For target-side queries: use the value of TransferTarget.target.datasource

(e.g. datasource="ch_prod"). If the SQL needs to disambiguate a database or schema inside that connector, qualify it in the query (e.g. FROM <db>.<schema>.<table>). Never pass the strings "source"/"target" — those are not real datasource keys and execute_sql will route to the wrong connector.

• Source database is read-only. The default validator should not query it.
• Report the row-count and target-query checks only. Keep failures concrete.

Checklist

Run these lightweight checks for each TransferTarget.

1. Row Count Parity

Compare the tool-reported counts:

• source_row_count
• transferred_row_count

Fail if both are present and differ. Do not re-run the source query.

2. Target Row Count

Run one target-side count query using the concrete target datasource and table coordinates from the TransferTarget.

SELECT COUNT(*) AS row_count
FROM {target_table};

Compare the result with transferred_row_count. This is blocking when the target count cannot be read or does not match the transferred count.

3. Target Sample

Optionally read a small sample to confirm the target table is queryable.

SELECT *
FROM {target_table}
LIMIT 5;

Treat this as advisory unless the query itself fails.

Out Of Scope For The Built-In Skill

Do not run null-ratio, min/max, distinct-count, duplicate-key, sample-diff, or numeric-aggregate checks here. Those checks can be added later as project-specific validator skills with their own cost profile and table contracts.

Output

Emit the JSON report block that ValidationHook expects — see the output contract appended to this skill at invocation time by the hook.