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Datasets:
codeslord
/
skilltrainbench-public

Tasks:
Other
Tags:
agents
agentic-benchmark
harbor
training-split
Libraries:
Harbor
License:
Dataset card Files
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Dataset Viewer
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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
npv: double
fixed_leg_pv: double
float_leg_pv: double
pv01: double
pay_receive: string
libor_10y_par_swap_rate: double
ois_5y_zero_rate_continuous: double
ois_10y_zero_rate_continuous: double
libor_5y_zero_rate_continuous: double
libor_10y_zero_rate_continuous: double
max_bootstrap_residual_bps: double
to
{'ois_5y_zero_rate_continuous': Value('float64'), 'ois_10y_zero_rate_continuous': Value('float64'), 'libor_5y_zero_rate_continuous': Value('float64'), 'libor_10y_zero_rate_continuous': Value('float64'), 'libor_10y_par_swap_rate': Value('float64'), 'max_bootstrap_residual_bps': Value('float64')}
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
              npv: double
              fixed_leg_pv: double
              float_leg_pv: double
              pv01: double
              pay_receive: string
              libor_10y_par_swap_rate: double
              ois_5y_zero_rate_continuous: double
              ois_10y_zero_rate_continuous: double
              libor_5y_zero_rate_continuous: double
              libor_10y_zero_rate_continuous: double
              max_bootstrap_residual_bps: double
              to
              {'ois_5y_zero_rate_continuous': Value('float64'), 'ois_10y_zero_rate_continuous': Value('float64'), 'libor_5y_zero_rate_continuous': Value('float64'), 'libor_10y_zero_rate_continuous': Value('float64'), 'libor_10y_par_swap_rate': Value('float64'), 'max_bootstrap_residual_bps': Value('float64')}
              because column names don't match

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skilltrainbench training tasks

The training half of the skilltrainbench benchmark suite: for each of the four datasets, the dev_task_names of its pinned train/test split, in Harbor task format.

The held-out/test tasks are not in this repository. Neither are the published splits that are not the pin, nor the tasks that fall outside each pinned split's task set. Use this repository for skill formation and training; evaluate on the held-out half, which stays in the private source repository.

Dataset Pinned split Task set Train tasks here Held-out (absent)
healthbench hb-hardbeh-s002 hard_behavioural 200 160
hle hle-stem517-s001 stem517 412 105
QuantitativeFinance-Bench qf-medhard-strat-80-s005 medium_hard 54 14
tau3-bench tau3-banking-70-s001 banking_knowledge 67 30
Total 733 309

Layout 

<dataset>/
  README.md        dataset card: scoring, judge configuration, provenance
  LICENSE          upstream licence, where the upstream declares one
  dataset.toml     manifest, filtered to the tasks present here
  tasks/<name>/    one directory per training task
splits/
  README.md        the pin table, learner pools and tool-call cutoffs
  <dataset>/       the pinned split file, reproduced byte-for-byte

Each split file keeps both dev_task_names and heldout_task_names so that its assignment_sha256 still verifies against the digests in splits/README.md. The held-out names therefore resolve to directories that are not in this repository.

dataset.toml in each dataset folder has been filtered to the tasks present; every other file is byte-identical to the source repository.

Download

Everything:

hf download armin-aptura/skilltrainbench-public --repo-type dataset --local-dir .

One dataset and its split:

hf download armin-aptura/skilltrainbench-public --repo-type dataset \
  --include "tau3-bench/**" --include "splits/tau3-bench/**" --local-dir .

Licensing

Licensing is per dataset folder, not uniform across this repository. Check the folder you intend to use.

Dataset Licence Attribution
QuantitativeFinance-Bench CC BY-NC 4.0 (LICENSE) QF-Bench
healthbench MIT (LICENSE) OpenAI
tau3-bench MIT (LICENSE) Sierra Research
hle no LICENSE file in this folder harbor-framework/harbor-datasets

QuantitativeFinance-Bench is non-commercial.

QuantitativeFinance-Bench tasks carry a canary GUID, documented in its README, so that contamination of a model's training corpus can be detected.

Provenance

Derived from the private repository skilltrainbench/dataset at revision b1d7426f376c6310246323801e8d490582d39276. Each dataset folder's own README records the upstream source, generator commit and task-tree digest.
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