AI Analysis
Final verdict: SAFE
The package shows minimal risk indicators with no network calls, shell executions, obfuscations, or credential risks. However, the metadata suggests a potentially less experienced maintainer, which slightly increases the risk score.
- Low network and execution risks
- Potential novice maintainer
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require internet access.
- Shell: No shell execution patterns detected, indicating the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has a new or inactive account and lacks a proper author name, which could indicate low activity or a less experienced user.
Package Quality Overall: Low (2.8/10)
○ Low
Test Suite
1.0
No test suite detected
No test files or test-runner configuration detected
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (1861 chars)
○ Low
Contributing Guide
2.0
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
○ Low
Type Annotations
1.0
No type annotations detected
No type annotations, py.typed marker, or stub files detected
◈ Medium
Multiple Contributors
5.0
Limited contributor diversity
1 unique contributor(s) across 100 commits in artanis-ai/gravelSingle author but highly active (100 commits)
Heuristic Checks
Outbound Network Calls
No suspicious network call patterns found
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
No shell execution patterns detected
Credential Harvesting
No credential harvesting patterns detected
Typosquatting
No typosquatting candidates detected
Registered Email Domain
Email domain looks legitimate: artanis.ai>
Suspicious Page Links
All external links appear legitimate
Git Repository History
Repository artanis-ai/gravel appears legitimate
Maintainer History
score 4.0
2 maintainer concern(s) found
Author name is missing or very shortAuthor "" appears to have only 1 package on PyPI (new or inactive account)
Known CVE Vulnerabilities
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Use this prompt to build a project with artanis-gravel
Create a mini-application called 'PromptCraft' that helps AI developers manage, trace, and evaluate their prompts more effectively using the 'artanis-gravel' package. This application will allow users to create, edit, and store prompts for various AI models, track the performance of these prompts over time, and conduct evaluations based on predefined metrics. Here are the key steps and features: 1. **Setup**: Initialize the project with the necessary dependencies including 'artanis-gravel'. Ensure that 'artanis-gravel' is correctly installed and imported into your Python environment. 2. **Prompt Management**: Implement a feature that allows users to input new prompts, modify existing ones, and delete them if needed. Each prompt should have metadata such as creation date, last modified date, and associated AI model name. 3. **Prompt Tracing**: Integrate 'artanis-gravel' to enable logging of each prompt's usage across different sessions. This will help in understanding how often a specific prompt is used and under what conditions. 4. **Evaluation Framework**: Develop an evaluation system where users can define criteria to assess the effectiveness of their prompts. These criteria could include response time, accuracy, and relevance. Use 'artanis-gravel' to automatically collect data during evaluations. 5. **Visualization**: Create visual representations of the collected data to make it easier for users to analyze the performance of their prompts. Consider using libraries like matplotlib or seaborn for this purpose. 6. **User Interface**: Design a simple but effective user interface using a web framework like Flask or Django. The UI should facilitate easy interaction with all the functionalities mentioned above. 7. **Documentation**: Provide comprehensive documentation explaining how to use PromptCraft, including setup instructions, API reference, and examples of how to integrate it into existing workflows. By following these steps and utilizing the capabilities of 'artanis-gravel', you'll develop a robust tool that significantly enhances the efficiency and effectiveness of AI prompt management and evaluation.
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