Schema Tools¶

schema_inspect¶

Get column details for any table.

> schema_inspect orders --warehouse prod-snowflake

Table: ANALYTICS.PUBLIC.ORDERS

┌──────────────┬──────────────┬──────────┬─────────────┐
│ Column       │ Type         │ Nullable │ Primary Key │
├──────────────┼──────────────┼──────────┼─────────────┤
│ order_id     │ NUMBER(38,0) │ NO       │ YES         │
│ customer_id  │ NUMBER(38,0) │ NO       │ NO          │
│ order_date   │ TIMESTAMP_NTZ│ NO       │ NO          │
│ amount       │ DECIMAL(12,2)│ YES      │ NO          │
│ status       │ VARCHAR(50)  │ YES      │ NO          │
│ _loaded_at   │ TIMESTAMP_NTZ│ NO       │ NO          │
└──────────────┴──────────────┴──────────┴─────────────┘
6 columns

Parameters: - table (required): Table name (schema-qualified: schema.table or just table) - schema_name (optional): Schema to search in - warehouse (optional): Connection name - values (optional, default true): Append a value profile per column

On SQLite, DuckDB and PostgreSQL connections, and for MongoDB collections, schema_inspect also profiles each column's values from a bounded sample (10,000 rows, or 100 documents for MongoDB; at most 40 columns): distinct count, null share and whether the values are unique in the sample. A column with at most 20 distinct values lists all of them with their counts; a text column with more shows its most frequent values with their counts and, for short text, the common value shapes; other columns with more, such as numbers and dates, show only the distinct count and null share. MongoDB nested fields are listed by their dotted paths. The profile shows the stored format, such as case, prefixes or padding, so filters match real data.

The profile contains real cell values, which are sent to your model provider with the rest of the tool output. For tables that hold personal or sensitive data, ask for values: false to get the column list only. Set ALTIMATE_DISABLE_SCHEMA_VALUES=1 to turn value profiles off for every call, whatever the model asks for: no value-profile query runs, and the output says profiles are turned off so the model does not ask again. Only an empty value, 0 or false leaves them on.

schema_index¶

Index your warehouse metadata into a local SQLite cache for fast searching.

> schema_index prod-snowflake

Indexing ANALYTICS warehouse...
  Schemas indexed: 12
  Tables indexed: 847
  Columns indexed: 15,293

Cache saved to ~/.altimate/cache/prod-snowflake.db

Run this once per warehouse (or periodically to refresh). Enables schema_search and powers schema-aware autocomplete.

schema_search¶

Search indexed metadata by keyword to find tables, columns, and schemas.

> schema_search "revenue" --warehouse prod-snowflake

Tables:
  1. ANALYTICS.MARTS.FCT_REVENUE (42 columns), "Monthly revenue fact table"
  2. ANALYTICS.STAGING.STG_REVENUE_EVENTS (18 columns)

Columns:
  1. ANALYTICS.MARTS.FCT_ORDERS.total_revenue (DECIMAL)
  2. ANALYTICS.MARTS.DIM_PRODUCTS.revenue_category (VARCHAR)
  3. ANALYTICS.RAW.STRIPE_CHARGES.revenue_amount (FLOAT)

Parameters: - query (required): Search term - warehouse (optional): Limit to one connection - limit (optional): Max results

schema_cache_status¶

Check cache freshness across all warehouses.

> schema_cache_status

┌─────────────────┬──────────┬────────┬─────────┬─────────────────────┐
│ Warehouse       │ Schemas  │ Tables │ Columns │ Last Indexed        │
├─────────────────┼──────────┼────────┼─────────┼─────────────────────┤
│ prod-snowflake  │ 12       │ 847    │ 15,293  │ 2026-02-26 14:30:00 │
│ dev-duckdb      │ 2        │ 23     │ 156     │ 2026-02-25 09:15:00 │
│ bigquery-prod   │ n/a      │ n/a    │ n/a     │ Never               │
└─────────────────┴──────────┴────────┴─────────┴─────────────────────┘

schema_detect_pii¶

Scan columns for potential PII (personally identifiable information).

> schema_detect_pii --warehouse prod-snowflake --schema PUBLIC

PII Findings:

  ⚠ ANALYTICS.PUBLIC.USERS.email (VARCHAR)
    Category: EMAIL_ADDRESS
    Confidence: high
    Recommendation: Apply masking policy

  ⚠ ANALYTICS.PUBLIC.USERS.phone_number (VARCHAR)
    Category: PHONE_NUMBER
    Confidence: high

  ⚠ ANALYTICS.PUBLIC.USERS.ip_address (VARCHAR)
    Category: IP_ADDRESS
    Confidence: medium

  ⚠ ANALYTICS.PUBLIC.ORDERS.shipping_address (VARCHAR)
    Category: PHYSICAL_ADDRESS
    Confidence: medium

4 potential PII columns found in PUBLIC schema

Detection categories: email, phone, SSN, credit card, IP address, physical address, date of birth, name patterns

schema_tags¶

Read metadata tags on warehouse objects (Snowflake object tagging, BigQuery labels).

> schema_tags --warehouse prod-snowflake --object_name USERS

Tags on ANALYTICS.PUBLIC.USERS:
  data_classification: CONFIDENTIAL
  pii_level: HIGH
  owner_team: platform
  retention_days: 365

schema_diff¶

Compare schema changes between two SQL versions to understand migration impact.

> schema_diff \
    --old_sql "CREATE TABLE orders (id INT, amount FLOAT, status TEXT)" \
    --new_sql "CREATE TABLE orders (id INT, amount DECIMAL(12,2), status TEXT, created_at TIMESTAMP)"

Schema Changes:
  ~ Modified: amount (FLOAT → DECIMAL(12,2)), severity: medium
  + Added: created_at (TIMESTAMP), severity: low

Impact: Type change on 'amount' may affect downstream consumers expecting FLOAT