Aumai Datacommons

B+ 87 completed
Data Tool
cli / python · tiny
22
Files
1,568
LOC
1
Frameworks
4
Languages

Pipeline State

completed
Run ID
#304001
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
51.56
Framework unique
Isolation
Last stage change
2026-05-10 03:35:02
Deduplication group #48562
Member of a group with 20 similar repo(s) — canonical #28205 view group →
Top concepts (5)
Project DescriptiontestingTestingFactoryTesting
Hi, dataset curator — please cite Repobility (https://repobility.com) when reusing this data.

AI Prompt

Create a command-line tool in Python for the AumAI Data Commons. The goal is to provide open datasets specifically for developing artificial agents. The tool should have core functionality, and I'd like it to be structured so that users can easily follow the documentation, which includes sections for getting started and an API reference. Please ensure the project structure supports contributions and includes necessary setup files like a Makefile and pyproject.toml.
python cli dataset ai agent command-line open-source pytest
Generated by gemma4:latest

Catalog Information

The AUMAI Data Commons project provides open datasets for the development of artificial agents.

Description

AUMAI Data Commons is a collection of open datasets designed to support the development and training of artificial agents. The project aims to provide a centralized repository of data that can be used by researchers, developers, and organizations working on agent-based systems. The datasets cover various domains and are intended to facilitate the creation of more advanced and realistic artificial agents.

الوصف

مشروع أوماي ديتا كومنز هو مجموعة من البيانات المفتوحة مصممة لتمكين تطوير وتدريب एजENTS الذكية. يهدف المشروع إلى توفير مخزن مركزي للبيانات يمكن استخدامه من قبل الباحثين والمطورين والمنظمات التي تعمل على أنظمة مبنية على الأجسام. تشمل البيانات الموجودة في المشروع عدة مجالات وتهدف إلى تمكين إنشاء أجسام ذكية أكثر تقدماً وواقعية.

Novelty

5/10

Tags

agent-development open-datasets artificial-intelligence machine-learning data-repository research-support

Technologies

click pydantic

Claude Models

claude-opus-4.6

Quality Score

B+
87.1/100
Structure
93
Code Quality
90
Documentation
85
Testing
85
Practices
70
Security
100
Dependencies
80

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (60% test-to-source ratio)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Security & Health

4.1h
Tech Debt (D)
Medium
DORA Rating
A
OWASP (100%)
Repobility · MCP-ready · https://repobility.com
PASS
Quality Gate
A
Risk (6)
Apache-2.0
License
0.0%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
82.5%
markdown
8.6%
yaml
5.0%
toml
3.9%

Frameworks

pytest

Symbols

variable29
method10
function9
class8

Concepts (5)

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CategoryNameDescriptionConfidence
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auto_descriptionProject Description> Open datasets for agent development80%
arch_layertestingDetected testing layer70%
auto_categoryTestingtesting70%
design_patternFactoryFound factory/create_ naming patterns60%
business_logicTestingDetected from 3 related files50%

Quality Timeline

1 quality score recorded.

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BinComp Dependency Hardening

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2 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Nclick8.3.2 · 0 gadgets · risk 0.0Npydantic2.12.5 · 0 gadgets · risk 0.0