Datasets:

FWeindel
/

validated-tasks

language:
  - en
task_categories:
  - text-generation
tags:
  - agent
  - code
  - agentic-tasks
  - harbor
  - reinforcement-learning
configs:
  - config_name: default
    data_files:
      - split: train
        path: '*_v1/tasks.parquet'
  - config_name: v2
    data_files:
      - split: train
        path: '*_v2/tasks.parquet'
  - config_name: archive
    data_files:
      - split: train
        path: '*_v1/archive.parquet'

Validated tasks

Datasets repaired and filtered using the OT-next-data validation protocol.

V1: environment reliability and rule-based task-quality repairs. Build/setup, no-op and reference checks where reference solutions exist.
V2: keep tasks solved at least once by an evaluated model. Includes partial results where a success is already recorded; each README lists models, attempt counts and coverage.

Dataset sizes and composition

V1: 42,166 kept, patched tasks across 8 data sources.

V2: 7,684 tasks solved at least once across the same 8 data sources. V2 is a subset of V1, not additional tasks.

Percentages are each source's share of that version's total in the current published snapshots.

Dataset	V1 tasks	Share of V1	V2 tasks	Share of V2
BugsInPy	489	1.16%	65	0.85%
CrossCodeEval	6,710	15.91%	863	11.23%
TermiGen	3,336	7.91%	2,277	29.63%
SETA	3,107	7.37%	2,205	28.70%
CalibForge	5,317	12.61%	84	1.09%
ScaleSWE	16,786	39.81%	292	3.80%
SWE-Lego	4,277	10.14%	575	7.48%
EndlessTerminals	2,144	5.08%	1,323	17.22%
Total	42,166	100%	7,684	100%

tasks.parquet contains kept tasks, archive.parquet archived ones. ScaleSWE still uses its original Docker Hub images; we haven't consolidated them into shared images yet.

Download tasks and images

from huggingface_hub import snapshot_download

snapshot_download(
    "FWeindel/validated-tasks",
    repo_type="dataset",
    allow_patterns=["seta_v2/tasks.parquet", "seta_v1/cached_images/**"],
    local_dir="data",
)

Trace stats

Trace stats put each attempt into one outcome category:

Outcome	Meaning
Task complete	The agent said it was done and confirmed that it wanted to finish. The verifier still checks whether the solution is correct.
tmux session closed	The terminal closed before normal completion, for example because the agent sent an `exit` command or killed tmux.
Task timeout	The agent ran out of time.
Repeated output truncation	Three responses in a row were too long (current default: 8,192 output tokens) and could not be used.
Other limits	The agent hit another limit, such as the number of turns, response length, context size or task memory.
Environment error	The container could not start, or a terminal command or communication failed. Confirmed terminal closures go under “tmux session closed.”
Verifier error	The checker could not run or finish normally. A solution simply failing its tests is not a verifier error.
Model server error	A request to the model failed, for example because the server was unavailable or the request timed out.
Harness error	The software running the agent failed, for example because of a bug in retry handling.
Other error	An error was recorded, but it does not fit the categories above.
Not recorded	The saved result does not say how the attempt ended.

These labels come from the harness's recorded stop reason and error type, not an LLM judge.