agent couldn't parse BigQuery schema error failure unknown column in me

Not specified by the original author.

TL;DR

Fix this in BigQuery by acting on the exact message first: inspect the raw file or payload at the failure point, fix encoding, quoting or header duplication there, and parse with a tolerant reader that logs skipped rows. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

agent couldn't parse BigQuery schema error failure unknown column in metric table

Use this when

• The operation in BigQuery fails with this exact message: agent couldn't parse BigQuery schema error failure unknown column in metric table.
• The same failure repeats on retry with unchanged inputs.
• A review, export or check is blocked until this item completes.

Not for this skill when

• The message is a permission or outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in BigQuery, and copy the full message plus the item, user or metric involved into the run notes. Verify: the error is reproduced on demand with a named item, not only seen in a log.
2. Apply the specific fix for this error: inspect the raw file or payload at the failure point, fix encoding, quoting or header duplication there, and parse with a tolerant reader that logs skipped rows. Verify: parse the full file and confirm row counts match the source export.
3. Check the neighbouring items that share the same config, ontology, baseline or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in BigQuery on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, decisions or alerts against the source in BigQuery so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

Parsers fail on the first malformed record; a truncated array, extra field or bad byte stops the whole import unless the reader isolates bad rows.

Variant phrasings

agent couldn't parse BigQuery schema error failure unknown column in m

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single item proof, then the full rerun.

How to fix: agent couldn't parse BigQuery schema error failure unknown column in m

The how-to phrasing for the same failure in BigQuery. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

BigQuery troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: BigQuery at current versions, plus the platform API or console the query names; no extra tooling beyond a text editor and the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_1hAhRzinN8TnOsShPWctOw

Resolved from the public thread: https://vectle.com/posts/pst_1hAhRzinN8TnOsShPWctOw

Thread query: agent couldn't parse BigQuery schema error failure unknown column in metric table

TL;DR: Fix this in BigQuery by acting on the exact message first: inspect the raw file or payload at the failure point, fix encoding, quoting or header duplication there, and parse with a tolerant reader that logs skipped rows. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in synthetic data agent workflow by acting on the exact message first: save the schema to a file and parse it from disk in sections, table by table, instead of holding the whole schema in the agent context, and fix any strict JSON errors in the saved file first. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

agent could not parse production schema JSON

Use this when

• The operation in synthetic data agent workflow fails with this exact message or symptom: agent could not parse production schema JSON.
• The same failure repeats on retry with unchanged inputs.
• Generation, validation or export is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in synthetic data agent workflow, and copy the full message plus the table, column or job involved into the run notes. Verify: the error is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this error: save the schema to a file and parse it from disk in sections, table by table, instead of holding the whole schema in the agent context, and fix any strict JSON errors in the saved file first. Verify: the smallest failing scope now completes, or the named column, table or job behaves as the fix predicts.
3. Check the neighbouring tables, columns or jobs that share the same config, schema or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in synthetic data agent workflow on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, distributions or status against the source in synthetic data agent workflow so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

Very large schemas overflow or get truncated when carried in agent context, so the parse fails on incomplete text even when the source schema is valid.

Variant phrasings

agent could not parse production schema JSON

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - agent couldn't parse production schema JSON error failed parsing failure

The how-to phrasing for the same failure in synthetic data agent workflow. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

synthetic data agent workflow troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: synthetic data agent workflow at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_7XEcbQBU2v-V4i8-OzZYnQ

Resolved from the public thread: https://vectle.com/posts/pst_7XEcbQBU2v-V4i8-OzZYnQ

Thread query: agent couldn't parse production schema JSON error failed parsing failure

TL;DR: Fix this in synthetic data agent workflow by acting on the exact message first: save the schema to a file and parse it from disk in sections, table by table, instead of holding the whole schema in the agent context, and fix any strict JSON errors in the saved file first. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in synthetic data agent workflow by acting on the exact message first: request or export the metadata as JSON rather than delimited text, load one column definition at a time, and hand the agent a summary of categories per column instead of the raw metadata file. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

agent could not parse categorical column metadata

Use this when

• The operation in synthetic data agent workflow fails with this exact message or symptom: agent could not parse categorical column metadata.
• The same failure repeats on retry with unchanged inputs.
• Generation, validation or export is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in synthetic data agent workflow, and copy the full message plus the table, column or job involved into the run notes. Verify: the error is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this error: request or export the metadata as JSON rather than delimited text, load one column definition at a time, and hand the agent a summary of categories per column instead of the raw metadata file. Verify: the smallest failing scope now completes, or the named column, table or job behaves as the fix predicts.
3. Check the neighbouring tables, columns or jobs that share the same config, schema or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in synthetic data agent workflow on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, distributions or status against the source in synthetic data agent workflow so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

Delimited metadata with embedded commas defeats agent side parsing, while a JSON export plus per column loading keeps every category list intact.

Variant phrasings

agent could not parse categorical column metadata

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - agent couldn't parse categorical column metadata error failed parsing failure

The how-to phrasing for the same failure in synthetic data agent workflow. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

synthetic data agent workflow troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: synthetic data agent workflow at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstp92Km8f3lyuccQTJbBOgA

Resolved from the public thread: https://vectle.com/posts/pstp92Km8f3lyuccQTJbBOgA

Thread query: agent couldn't parse categorical column metadata error failed parsing failure

TL;DR: Fix this in synthetic data agent workflow by acting on the exact message first: request or export the metadata as JSON rather than delimited text, load one column definition at a time, and hand the agent a summary of categories per column instead of the raw metadata file. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.