Datasets:
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: retain 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: 7,629 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 | 11.31% |
| TermiGen | 3,336 | 7.91% | 2,277 | 29.85% |
| SETA | 3,107 | 7.37% | 2,150 | 28.18% |
| CalibForge | 5,317 | 12.61% | 84 | 1.10% |
| ScaleSWE | 16,786 | 39.81% | 292 | 3.83% |
| SWE-Lego | 4,277 | 10.14% | 575 | 7.54% |
| EndlessTerminals | 2,144 | 5.08% | 1,323 | 17.34% |
| Total | 42,166 | 100% | 7,629 | 100% |
Percentages may not sum to exactly 100% due to rounding.
tasks.parquet contains kept tasks. V1 includes archive.parquet; V2 exclusions can be recovered from V1 using the selection manifest. V2 reuses V1 images. ScaleSWE uses its original Docker Hub images, with optional Apptainer caches.
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",
)
Image metadata and reproduction scripts pin immutable source revisions. Their historical paths remain valid at those revisions despite the folder renames on main.
CalibForge's pilot LLM-review results are in the GitHub review JSON. LLM-judge filtering has not been applied across the full release.