Synthetic data factory: Grok 4.6
Collection
Grok 4.6 synthetic agentic factory. Not for Spikenaut. Not from Fable 5. • 44 items • Updated
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
id: string
goal: string
plan: string
true_root_cause: string
red_herring: string
forbidden_diagnosis: string
required_evidence: list<item: string>
child 0, item: string
steps: list<item: string>
child 0, item: string
outcome: string
reward: struct<success: bool, red_herring_dismissed: int64, forbidden_diagnosis_avoided: bool, replica_lag_s (... 241 chars omitted)
child 0, success: bool
child 1, red_herring_dismissed: int64
child 2, forbidden_diagnosis_avoided: bool
child 3, replica_lag_s_before: int64
child 4, replica_lag_s_after: double
child 5, p99_s_before: double
child 6, p99_s_after: double
child 7, analytics_select_killed: bool
child 8, cost_steps: int64
child 9, wrong_mitigation_rollback: int64
child 10, handoff_dba: bool
child 11, writer_dns_updated: bool
child 12, five_xx_rps_end: double
meta: struct<factory: string, round: int64, generator: string, opensre_seed: string>
child 0, factory: string
child 1, round: int64
child 2, generator: string
child 3, opensre_seed: string
kind: string
false_lead: struct<claim: string, survived_steps: list<item: int64>, falsified_at: int64>
child 0, claim: string
child 1, survived_steps: list<item: int64>
child 0, item: int64
child 2, falsified_at: int64
rca: string
remediate: string
to
{'id': Value('string'), 'goal': Value('string'), 'plan': Value('string'), 'kind': Value('string'), 'steps': List(Json(decode=True)), 'outcome': Value('string'), 'reward': {'success': Value('bool'), 'steps': Value('int64'), 'false_lead_steps': Value('int64'), 'http_retries': Value('int64')}, 'false_lead': {'claim': Value('string'), 'survived_steps': List(Value('int64')), 'falsified_at': Value('int64')}, 'rca': Value('string'), 'remediate': Value('string'), 'meta': {'factory': Value('string'), 'round': Value('int64'), 'generator': Value('string'), 'plant': Value('string'), 'alert_source': Value('string'), 'ticket': Value('string')}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
id: string
goal: string
plan: string
true_root_cause: string
red_herring: string
forbidden_diagnosis: string
required_evidence: list<item: string>
child 0, item: string
steps: list<item: string>
child 0, item: string
outcome: string
reward: struct<success: bool, red_herring_dismissed: int64, forbidden_diagnosis_avoided: bool, replica_lag_s (... 241 chars omitted)
child 0, success: bool
child 1, red_herring_dismissed: int64
child 2, forbidden_diagnosis_avoided: bool
child 3, replica_lag_s_before: int64
child 4, replica_lag_s_after: double
child 5, p99_s_before: double
child 6, p99_s_after: double
child 7, analytics_select_killed: bool
child 8, cost_steps: int64
child 9, wrong_mitigation_rollback: int64
child 10, handoff_dba: bool
child 11, writer_dns_updated: bool
child 12, five_xx_rps_end: double
meta: struct<factory: string, round: int64, generator: string, opensre_seed: string>
child 0, factory: string
child 1, round: int64
child 2, generator: string
child 3, opensre_seed: string
kind: string
false_lead: struct<claim: string, survived_steps: list<item: int64>, falsified_at: int64>
child 0, claim: string
child 1, survived_steps: list<item: int64>
child 0, item: int64
child 2, falsified_at: int64
rca: string
remediate: string
to
{'id': Value('string'), 'goal': Value('string'), 'plan': Value('string'), 'kind': Value('string'), 'steps': List(Json(decode=True)), 'outcome': Value('string'), 'reward': {'success': Value('bool'), 'steps': Value('int64'), 'false_lead_steps': Value('int64'), 'http_retries': Value('int64')}, 'false_lead': {'claim': Value('string'), 'survived_steps': List(Value('int64')), 'falsified_at': Value('int64')}, 'rca': Value('string'), 'remediate': Value('string'), 'meta': {'factory': Value('string'), 'round': Value('int64'), 'generator': Value('string'), 'plant': Value('string'), 'alert_source': Value('string'), 'ticket': Value('string')}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Incident Response Oncall Trajectories
Release status: The raw, uncurated payload is now published under
data/raw/. It is available for inspection and reproducibility, but it is not training-ready.
Visibility: public raw-data repository.
On-call leftover-signal RCA trajectories.
Intended model target
This is a general agentic research dataset in the Grok 4.6 agentic factory. It is independent of the Fable 5 collection and is not labeled as Spikenaut training data.
Generation attribution
The underlying synthetic data is generated by Grok 4.6 through the
Synthetic Data Factory agentic lane. Factory slug:
incident-response-oncall-factory. Source tree:
outputs/raw/2026-08-19-agentic/incident-response-oncall-factory/.
Published raw payload
The release contains 7704 raw records across
data/raw/batch-r01.jsonl through data/raw/batch-r3852.jsonl (~64923 KB), snapshotted from
outputs/raw/2026-08-19-agentic/incident-response-oncall-factory/. Supporting notes are under
data/metadata/NOTES-*.md. The factory source remains the write destination; this Hub
copy is a public evidence snapshot, not the curated training export. Public
visibility is not a training-readiness claim.
Planned curated release
Curated training publication remains blocked until a later audit and export pass. Do not treat this repository as a training corpus.
Links
License
This public raw release is licensed under the Apache License 2.0. That license grants reuse permissions; it does not make the records training-ready or factual real-world measurements.
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