agent-def-translator

v0.1.2 safe
4.0
Medium Risk

Translate canonical coding-agent definitions into platform-native agent artifacts.

🤖 AI Analysis

Final verdict: SAFE

The package presents a relatively low risk profile with no network calls or credential harvesting observed. While there is a moderate shell risk due to its execution capabilities, and some metadata concerns regarding the author and repository activity, these factors alone do not strongly suggest malicious intent or a supply-chain attack.

  • No network calls detected
  • No credential harvesting patterns
  • Moderate shell risk due to execution capabilities
  • Unknown author and low activity in git repository
Per-check LLM notes
  • Network: No network calls detected, which is low risk.
  • Shell: Shell execution capability may be used for legitimate purposes but could also indicate potential for executing arbitrary commands, hence moderate risk.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
  • Credentials: No credential harvesting patterns detected, indicating low risk of secret theft.
  • Metadata: The package shows some red flags such as an unknown author and low activity in the git repository, but there is no clear evidence of malicious intent.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • ript(*args: str) -> None: subprocess.run( # noqa: S603 args, cwd=PROJECT_ROOT,
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: kitsuyui.com>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 2.5

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
⚠ Maintainer History score 4.0

2 maintainer concern(s) found

  • Author name is missing or very short
  • Author "" 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 agent-def-translator 
Create a mini-application named 'AgentCraft' that serves as a bridge between developers and various cloud platforms by translating standardized coding-agent definitions into native artifacts suitable for deployment on those platforms. This application will utilize the 'agent-def-translator' package to handle the translation process efficiently.

### Features:
1. **User-Friendly Interface**: A simple, intuitive interface where users can input their coding-agent definitions in a standardized format.
2. **Platform Selection**: Users should be able to select from a list of supported cloud platforms (e.g., AWS, Azure, GCP).
3. **Translation Process**: Upon selection of a platform, the application will use the 'agent-def-translator' package to convert the provided agent definition into a native artifact compatible with the chosen platform.
4. **Artifact Download**: After successful translation, the application should allow users to download the generated native artifact.
5. **Error Handling**: Implement robust error handling to manage any issues during the translation process, providing meaningful feedback to the user.
6. **Documentation**: Include comprehensive documentation within the application explaining the supported formats and platforms, along with examples.
7. **Logging**: Maintain logs of all translations performed for auditing and troubleshooting purposes.
8. **Version Control**: Allow users to save multiple versions of their agent definitions and view their translation history.

### Steps to Build AgentCraft:
1. **Setup Development Environment**: Ensure you have Python installed, and set up a virtual environment for your project.
2. **Install Dependencies**: Use pip to install the 'agent-def-translator' package along with other necessary libraries like Flask for the web framework.
3. **Design User Interface**: Develop a clean, responsive UI using HTML/CSS/JavaScript for frontend interaction.
4. **Backend Development**: Write backend logic using Python and the 'agent-def-translator' package to handle the translation process.
5. **Testing**: Thoroughly test the application with various agent definitions and platform selections to ensure reliability.
6. **Deployment**: Prepare a Dockerfile for containerizing the application and deploy it on a server or cloud platform of your choice.
7. **Maintenance and Updates**: Regularly update the application based on user feedback and new platform support requirements.

### Utilization of 'agent-def-translator':
- Import the 'agent-def-translator' package in your Python codebase.
- Use its functions to parse the standardized agent definition input from the user.
- Invoke the translation method provided by the package, passing the parsed data and selected platform as parameters.
- Handle the returned artifact and provide it to the user for download.

This project aims to simplify the process of deploying coding agents across different cloud environments, making it accessible even to those less familiar with platform-specific nuances.