historic-sql-table-digest

# Historic SQL Table Digest Use this skill when the WorkUnit raw file is one `tables/<schema>.<name>.json` file from the `historic-sql` adapter. ## Required Workflow 1. Read the WorkUnit notes first. 2. Call `read_raw_file` for the single `tables/<schema>.<name>.json` raw file. 3. Read `manifest.json` only if the table JSON omits the dialect or the WorkUnit notes are unclear. 4. Produce one concise usage narrative for this table from the staged table JSON. 5. Call `emit_historic_sql_evidence` exactly once with `kind: "table_usage"`. 6. Stop after the evidence tool succeeds. ## Identifier Verification Protocol Before writing a wiki page or SL source on any topic: 1. `discover_data({query: "<topic>"})` - see what wikis, SL sources, and raw tables already exist. Prefer updating existing pages over creating new ones. Before emitting any `schema.table` or `schema.table.column` into a wiki body, SL source, `tables:` frontmatter, `sl_refs`, or `emit_unmapped_fallback`: 2. `entity_details({connectionId, targets: [{display: "<identifier>"}]})` - confirm the identifier resolves; inspect native types, FK/PK, and sampleValues. 3. For literal values from the source, such as status codes or plan tiers, check whether they appear in `entity_details` sampleValues for the relevant column. If sampleValues is short or the sample may have missed real values, run a `sql_execution` probe with the same warehouse connection id: `sql_execution({connectionId, sql: "SELECT DISTINCT <col> FROM <ref> LIMIT 50"})`. 4. If the candidate identifier still does not resolve, do one of: - Use `sql_execution({connectionId, sql: "SELECT 1 FROM <ref> LIMIT 0"})`. If it errors, the identifier is fictional. - Wrap the identifier in `[unverified - from <rawPath>]` in the wiki body, citing the exact raw path that mentioned it. - When recording `emit_unmapped_fallback` with `no_physical_table`, include the failing probe error in `clarification`. 5. Never copy `<schema>.<table>` placeholder strings from these instructions into output. ## Evidence Shape Call `emit_historic_sql_evidence` with this shape: ```json { "kind": "table_usage", "table": "public.orders", "usage": { "narrative": "Orders are repeatedly queried for paid/refunded lifecycle analysis and customer-level rollups.", "frequencyTier": "high", "commonFilters": ["status", "created_at"], "commonGroupBys": ["status"], "commonJoins": [{ "table": "public.customers", "on": ["customer_id"] }], "staleSince": null } } ``` The `usage` object must match `tableUsageOutputSchema`. ## Interpretation Rules - Treat `columnsByClause.where` as common filters. - Treat `columnsByClause.groupBy` as common group-bys. - Treat `observedJoins` as common joins. - Use `stats.executionsBucket`, `stats.distinctUsersBucket`, and `stats.recencyBucket` to choose `frequencyTier`. - Use `frequencyTier: "high"` only when executions and distinct users are both broad. - Use `frequencyTier: "mid"` for repeated team usage that is not broad enough for high. - Use `frequencyTier: "low"` for low-volume but present usage. - Use `frequencyTier: "unused"` only when the table input explicitly says the table is stale or has no recent templates. - Keep `narrative` short and concrete. ## Boundaries - Do not call wiki_write. - Do not call sl_write_source. - Do not call sl_edit_source. - Do not call context_candidate_write. - Do not emit more than one table usage evidence object. - Do not invent columns, joins, or tables that are absent from the staged JSON.