SkillNet-Fabric
Collection
Official Skills, graphs, experiment results, and runtime logs for SkillNet-Fabric. • 1 item • Updated • 1
Dataset Preview
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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1531, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1405, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 982, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1393, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1571, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
json dict | __key__ string | __url__ string |
|---|---|---|
{
"bundles": {
"data_computation_task1": "d9ba031a2707df80dde74cd25a3430e66c6950cbd600de953a3fa448409a5bba",
"data_computation_task2": "d4ae7d2f28b7c0580c01f9ac2aa5036b209ab62c29deee549732f92a2634c373",
"data_computation_task3": "fa8ff034ae31ce92073bbe2e80509c400f40052d187901926b67c81d446a576e",
"data... | runs/analyses/agentskillos-ablation/bundles/bundle_manifest | hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/ablation/analysis-ablation.tar.zst |
{"bundles":null,"graph_closure_sha256":"21d638fef9f70279242a42cac4540a40e0071ce450da3f6cebe0031d42d2(...TRUNCATED) | runs/analyses/agentskillos-ablation/bundles/data_computation_task1 | "hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/(...TRUNCATED) |
{"bundles":null,"graph_closure_sha256":"21d638fef9f70279242a42cac4540a40e0071ce450da3f6cebe0031d42d2(...TRUNCATED) | runs/analyses/agentskillos-ablation/bundles/data_computation_task2 | "hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/(...TRUNCATED) |
{"bundles":null,"graph_closure_sha256":"21d638fef9f70279242a42cac4540a40e0071ce450da3f6cebe0031d42d2(...TRUNCATED) | runs/analyses/agentskillos-ablation/bundles/data_computation_task3 | "hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/(...TRUNCATED) |
{"bundles":null,"graph_closure_sha256":"21d638fef9f70279242a42cac4540a40e0071ce450da3f6cebe0031d42d2(...TRUNCATED) | runs/analyses/agentskillos-ablation/bundles/data_computation_task4 | "hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/(...TRUNCATED) |
{"bundles":null,"graph_closure_sha256":"21d638fef9f70279242a42cac4540a40e0071ce450da3f6cebe0031d42d2(...TRUNCATED) | runs/analyses/agentskillos-ablation/bundles/data_computation_task5 | "hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/(...TRUNCATED) |
{"bundles":null,"graph_closure_sha256":"21d638fef9f70279242a42cac4540a40e0071ce450da3f6cebe0031d42d2(...TRUNCATED) | runs/analyses/agentskillos-ablation/bundles/data_computation_task6 | "hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/(...TRUNCATED) |
{"bundles":null,"graph_closure_sha256":"21d638fef9f70279242a42cac4540a40e0071ce450da3f6cebe0031d42d2(...TRUNCATED) | runs/analyses/agentskillos-ablation/bundles/document_creation_task1 | "hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/(...TRUNCATED) |
{"bundles":null,"graph_closure_sha256":"21d638fef9f70279242a42cac4540a40e0071ce450da3f6cebe0031d42d2(...TRUNCATED) | runs/analyses/agentskillos-ablation/bundles/document_creation_task2 | "hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/(...TRUNCATED) |
{"bundles":null,"graph_closure_sha256":"21d638fef9f70279242a42cac4540a40e0071ce450da3f6cebe0031d42d2(...TRUNCATED) | runs/analyses/agentskillos-ablation/bundles/document_creation_task3 | "hf://datasets/zjunlp/SkillNet-Fabric@f5478dbc3c8c2e245f9ce5cd9651253bf00183e7/analysis_experiments/(...TRUNCATED) |
End of preview.
SkillNet-Fabric
This repository contains the released Skills and graphs, benchmark resources, and experiment artifacts for SkillFabric.
- Code: https://github.com/zjunlp/SkillNet-Fabric
- Artifacts: https://huggingface.co/datasets/zjunlp/SkillNet-Fabric
- Related SkillNet paper: https://arxiv.org/abs/2603.04448
Repository contents
| Path | Contents |
|---|---|
skills/ |
Skill corpus used to construct the released graphs |
data/ |
SkillRouter, SkillsBench, and AgentSkillOS benchmark inputs |
graphs/ |
G_SR, G_SB, G_A53, G_A500, G_A1K, and graph-build logs |
main_experiments/ |
Runs, results, evaluator records, deliverables, and logs for the three main experiments |
analysis_experiments/ |
Localization and ablation experiment artifacts |
artifact_index.json |
Bundle names, sizes, extraction targets, and checksums |
provenance.json |
Source checkout and release inventory |
Experiments included
| Experiment | Released artifacts |
|---|---|
| SkillRouter | SkillFabric routes, per-task scores, aggregate results, and runtime logs |
| SkillsBench | Two executors, 87 tasks, three trials, selected and runtime Skills, trajectories, verifier records, and deliverables |
| AgentSkillOS | Two executors, three Skill pools, task workspaces, generated frames, baseline artifacts, Bradley-Terry rankings, and runtime logs |
| Localization analysis | Routes, rankings, protocol, reports, and logs |
| AgentSkillOS ablation | Run outputs, rankings, reports, and logs |
The experiment directories preserve the run names used on the experiment server.
Download
Install the SkillNet-Fabric repository, then run:
skillfabric-repro download --repo-id zjunlp/SkillNet-Fabric --revision main --profile main
The command downloads the selected bundles and extracts them into experiments/artifacts/ using
the directory layout expected by the reproduction code.
Sources and licenses
- SkillRouter benchmark and evaluation: https://github.com/zhengyanzhao1997/SkillRouter and https://huggingface.co/datasets/pipizhao/SkillRouter-Eval-Core
- SkillRouter registry Skills:
majiayu000/claude-skill-registry, pinned by the released layer manifest - SkillsBench v1.1 tasks and evaluator: https://github.com/benchflow-ai/skillsbench
- AgentSkillOS tasks and evaluator: https://arxiv.org/abs/2603.02176
- Redistributed Skill packages: mixed-source snapshot; layer manifests record the source datasets and pinned upstream revisions
The repository LICENSE covers SkillFabric code. Released benchmark resources and redistributed
Skills retain their applicable upstream terms. Layer manifests preserve the available source and
license metadata.
Citation
Until the SkillFabric paper is public, cite the related SkillNet paper:
@article{liang2026skillnet,
title = {SkillNet: Create, Evaluate, and Connect AI Skills},
author = {Liang, Yuan and Zhong, Ruobin and Xu, Haoming and Jiang, Chen and others},
journal = {arXiv preprint arXiv:2603.04448},
year = {2026}
}
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