asimov-sim-lab

v0.1.0 safe
3.0
Low Risk

A spec-first MuJoCo inspection and validation workbench for the Asimov v1 simulation model.

🤖 AI Analysis

Final verdict: SAFE

The package has no network calls, minimal shell risks, and slightly concerning metadata suggesting low effort. However, these factors do not conclusively indicate malicious intent or a supply-chain attack.

  • No network calls detected
  • Git commands present, but benign
  • Low-effort metadata
Per-check LLM notes
  • Network: No network calls detected, indicating low risk.
  • Shell: Git commands suggest package is managing version control locally, which is generally benign.
  • Metadata: The package shows signs of low effort and could be from a new maintainer, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (4.8/10)

✦ High Test Suite 9.0

Test suite present — 20 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 20 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (8798 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 240 type-annotated function signatures detected in source
○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

  • No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 10.0

Found 6 shell execution pattern(s)

  • try: completed = subprocess.run( ["git", "-C", str(asset_root), *args],
  • (tmp_path: Path) -> None: subprocess.run(["git", "init"], cwd=tmp_path, check=True, capture_output=Tr
  • rue, capture_output=True) subprocess.run(["git", "config", "user.email", "[email protected]"], cwd=tmp
  • cwd=tmp_path, check=True) subprocess.run(["git", "config", "user.name", "Test"], cwd=tmp_path, check=
  • xt("x", encoding="utf-8") subprocess.run(["git", "add", "file.txt"], cwd=tmp_path, check=True) su
  • cwd=tmp_path, check=True) subprocess.run(["git", "commit", "-m", "init"], cwd=tmp_path, check=True, c
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

No GitHub repository linked

  • No GitHub repository link found
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • Author "Abdel" appears to have only 1 package on PyPI (new or inactive account)
  • Package has no PyPI classifiers (low effort / metadata quality)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with asimov-sim-lab 
Your task is to develop a user-friendly GUI-based application using Python that leverages the 'asimov-sim-lab' package to inspect and validate MuJoCo models specifically designed for the Asimov v1 simulation framework. This application will serve as a comprehensive tool for researchers and engineers working with robotic simulations. Here’s a detailed breakdown of the requirements and steps to achieve this goal:

1. **Project Setup**: Start by setting up your Python environment and installing the necessary packages, including 'asimov-sim-lab'. Ensure you have a compatible version of MuJoCo installed as well.

2. **Application Structure**: Design a modular application structure. Include components such as a main window, model loading interface, and result visualization area.

3. **Model Loading Interface**: Implement a feature that allows users to upload MuJoCo XML files (.xml) for inspection. Validate if the uploaded model adheres to the Asimov v1 standards using 'asimov-sim-lab'.

4. **Inspection Features**: Utilize 'asimov-sim-lab' to perform various inspections on the loaded model, such as checking for structural integrity, validating joint configurations, and ensuring collision detection works correctly.

5. **Result Visualization**: Develop a section within the GUI where the results of the inspections are displayed. Use charts, graphs, and textual summaries to present the findings clearly.

6. **Validation Reports**: Enable users to generate detailed validation reports based on the inspection results. These reports should be downloadable in PDF format.

7. **Interactive Simulation Preview**: Incorporate a feature that allows users to preview the loaded model in a simulated environment directly within the application. Use 'asimov-sim-lab' to drive the simulation and ensure it aligns with the expected behavior according to Asimov v1 specifications.

8. **User Interface Enhancements**: Make sure the GUI is intuitive and easy to navigate. Include tooltips, help sections, and error messages to assist users.

9. **Testing and Validation**: Thoroughly test the application with different MuJoCo models to ensure all functionalities work as expected. Pay special attention to edge cases and potential errors in model validation.

10. **Documentation**: Provide comprehensive documentation detailing how to use the application, including setup instructions, usage examples, and troubleshooting tips.

By following these steps, you'll create a powerful and user-friendly tool that significantly enhances the process of developing and validating MuJoCo models for Asimov v1 simulations.

💬 Discussion Feed

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