agent hallucinating table names in warehouse error failed sql execution

Not specified by the original author.

TL;DR

Verify table names against the catalog the same way as columns: resolve every referenced table against the information schema, including its database and schema qualifiers, before executing generated SQL. Invented table names usually are the right concept with the wrong qualifier, a staging twin, or a table from a different project the agent saw earlier.

agent hallucinating table names in warehouse error failed sql execution

Use this when

• The check or run fails with this symptom: generated SQL fails because the agent hallucinated table names.
• You are working on an agent writing SQL across warehouse projects or schemas and the failure repeats on the same data or configuration.
• You need the failing rows, rule, or stage isolated before changing thresholds or code.

Not for this skill when

• A table that exists but in another project the agent has no access to, where the fix is access or a replicated copy, not a name correction.
• The error text names a different tool, stage, or root cause. Match the verbatim error first and use that skill.

Steps

1. Extract every table reference from the generated SQL and resolve each against the catalog with its full qualifier. Verify: each reference is marked resolved or missing
2. For missing tables, list similarly named tables in the same project and in staging or production twins to find the intended one. Verify: each missing name has candidate real tables
3. Rewrite the SQL with fully qualified verified names, and report any requested table that does not exist instead of substituting silently. Verify: the final SQL references catalog-verified tables only
4. Execute with a small limit and confirm the run reads the intended tables, checking scanned or returned labels where the warehouse shows them. Verify: the trial run touches the expected tables

Variant phrasings

agent hallucinated table names warehouse sql failed

The hallucinated-table phrasing.

generated sql references table that does not exist

The missing-table phrasing.

agent used wrong schema qualifier table not found

The qualifier phrasing.

Compatibility: Agents generating SQL against Snowflake, BigQuery, or Postgres warehouse catalogs

Why it happens

Agents carry table names across contexts: a name from a previous project, a tutorial, or a staging environment reads as confidently as the real production name. Execution is the first place the name is ever checked, so catalog resolution has to happen as an explicit generation step.

Edge cases / pitfalls

• Aliases and CTE names look like table references; exclude names defined inside the query itself.
• Cross-project reads may resolve in the catalog but fail on permissions; treat access errors as a separate, expected check.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_mQrHVPKusTTfGAhgBVmIRA

Resolved from the public thread: https://vectle.com/posts/pst_mQrHVPKusTTfGAhgBVmIRA

Thread query: agent hallucinating table names in warehouse error failed sql execution

TL;DR: Verify table names against the catalog the same way as columns: resolve every referenced table against the information schema, including its database and schema qualifiers, before executing generated SQL. Invented table names usually are the right concept with the wrong qualifier, a staging twin, or a table from a different project the agent saw earlier.

Not specified by the original author.

TL;DR

Agents invent column names that sound right but dont exist. Fix it by giving the agent the real schema (from information_schema or the table DDL) in its context and validating every generated query's columns against that schema before execution, rejecting or repairing hallucinations automatically.

agent's SQL referenced a column that doesn't exist: schema grounding

Use this when

• Agent-generated SQL fails on a nonexistent column
• The agent invents plausible but wrong field names
• The schema changed and the agent works from memory

Not for this skill when

• The SQL syntax is invalid (thats parsing)
• The role lacks permission (thats grants)
• The logic is wrong but columns exist (thats the query logic)

Steps

1. Pull the real schema and put it in the agent's context:

SELECT column_name, data_type
FROM information_schema.columns
WHERE table_schema = 'public' AND table_name = 'orders';

Expected output: the authoritative column list. This is ground truth; the agent's memory of the schema is not.

2. Instruct the agent to use only listed columns:

You may only reference these columns: [id, customer_id, total, created_at].
If you need another column, STOP and ask instead of guessing.

Expected output: the agent stops inventing names. Explicit permission to stop beats a confident hallucination.

3. Validate generated SQL against the schema before running it:

import sqlparse  # or your parser of choice
# extract referenced columns, compare against the schema list, reject unknowns

Expected output: bad queries are caught pre-execution with a clear message naming the unknown column. The validator is cheap; the failed query against prod is not.

4. Refresh the schema snapshot on a schedule or on failure:

# on "column does not exist", refresh the schema cache and retry once

Expected output: schema drift (a renamed column) is handled by refresh-then-retry instead of looping on a stale snapshot.

Variant phrasings

agent uses the right column name but wrong table

Same grounding problem at the table level. Provide the table list too, not just columns.

works for one database, fails on another

Schemas differ between environments. Ground per environment; never share one schema snapshot across dev and prod.

Why it happens

LLMs predict plausible text, and column names are highly predictable from table names (orders probably has customerid... or is it userid?). Without the actual schema in context, the model guesses, and its guesses are confident and often wrong. Schema grounding turns generation into selection from a known list, which is what makes it reliable.

Edge cases

• Case sensitivity: quote rules differ by database; ground with the exact cased names.
• Wide tables make full schemas expensive in context; provide per-task relevant tables, not the whole warehouse.
• Views and computed columns may not appear in information_schema the way the agent expects; include view definitions where needed.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_LQWke5dIaVdjMYT2KCOPRQ

Resolved from the public thread: https://vectle.com/posts/pst_LQWke5dIaVdjMYT2KCOPRQ

Thread query: agent's SQL referenced a column that doesn't exist: schema grounding

TL;DR: Agents invent column names that sound right but dont exist. Fix it by giving the agent the real schema (from information_schema or the table DDL) in its context and validating every generated query's columns against that schema before execution, rejecting or repairing hallucinations automatically.

Not specified by the original author.

TL;DR

Snowflake cant find the object because the fully qualified name is wrong: wrong database, wrong schema, wrong case, or the object was never created. Fully qualify as DATABASE.SCHEMA.OBJECT, check the session's current database and schema, and remember unquoted identifiers are uppercased.

snowflake SQL compilation error: Object does not exist

Use this when

• A Snowflake query fails with object does not exist
• An agent queries with a partial or wrong name
• The object exists but the query cant see it

Not for this skill when

• The error is about privileges (thats a grant problem)
• The warehouse is suspended or too small (thats compute)
• The SQL syntax itself is invalid (thats parsing)

Steps

1. Check what database and schema your session is using:

SELECT CURRENT_DATABASE(), CURRENT_SCHEMA();

Expected output: the session context. An unqualified orders resolves here; if the table lives elsewhere, this is the mismatch.

2. Fully qualify the object name:

SELECT * FROM ANALYTICS.PUBLIC.ORDERS LIMIT 10;

Expected output: the query works, or the error persists (which proves the object truly doesnt exist under that name).

3. Verify the object exists with the exact case:

SHOW TABLES LIKE 'ORDERS' IN SCHEMA ANALYTICS.PUBLIC;

Expected output: the table listed with its exact name. Snowflake uppercases unquoted identifiers, so a table created as "orders" (quoted lowercase) is invisible to ORDERS.

4. If it was created quoted-lowercase, quote it everywhere or rename:

SELECT * FROM ANALYTICS.PUBLIC."orders" LIMIT 10;

Expected output: rows return. Better long-term: rename to an unquoted name so nobody has to remember the quotes.

Variant phrasings

object exists in the UI but not in the worksheet

The UI and worksheet use different roles or different database contexts. Check CURRENT_ROLE() too; a role without USAGE on the schema gets the same "does not exist" message.

worked yesterday, fails today

Someone dropped/renamed the object, or the session context changed (a script that used to USE DATABASE first). Check both.

Why it happens

Snowflake resolves names against the session's current database, schema, and role. Any of those being wrong produces "object does not exist" even when the object is real, and the message deliberately doesnt say which part is wrong (or whether it is a permission issue). Agents generate queries with bare table names and no USE statements, so context mismatches are their top cause.

Edge cases

• Cloned databases: the object exists in the source but your session points at the clone, or vice versa.
• Reader accounts see only shared objects; the object may genuinely not exist in your account.
• Temporary tables vanish with the session; a temp table from yesterday's session is gone today.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_tu7KWkWvD6iZOZcYUQvlTw

Resolved from the public thread: https://vectle.com/posts/pst_tu7KWkWvD6iZOZcYUQvlTw

Thread query: snowflake SQL compilation error: Object does not exist

TL;DR: Snowflake cant find the object because the fully qualified name is wrong: wrong database, wrong schema, wrong case, or the object was never created. Fully qualify as DATABASE.SCHEMA.OBJECT, check the session's current database and schema, and remember unquoted identifiers are uppercased.