🤖 AI Analysis

Final verdict: SAFE

The package has minimal risks with no network calls, shell execution anomalies, or obfuscation. Although the metadata quality is low and the coverage is only 66%, these factors alone do not suggest malicious intent.

No network calls detected
Standard shell execution patterns
Low obfuscation risk
Metadata quality and coverage could be improved

Per-check LLM notes

Network: No network calls detected, which is normal and not indicative of malicious activity.
Shell: Shell execution patterns are typical for building and packaging Python projects, indicating standard build process activities.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows signs of being newly created and having low metadata quality, but there are no clear red flags indicating malicious intent.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 4.0

Found 2 shell execution pattern(s)

=True) # Build wheel subprocess.check_call( [sys.executable, "setup.py", "bdist_wheel", "-d", s
ents=True, exist_ok=True) subprocess.check_call( [ sys.executable, "-m",

✓ 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

Repository bigmoon-dev/agent-cooking-cli appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "triageflow" 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 agent-cooking-cli

Develop a mini-application called 'BugSavior' using the Python package 'agent-cooking-cli'. This application aims to streamline the process of bug triage and management for developers working on CLI-based projects. Here’s a detailed breakdown of the application's requirements and features:

1. **User Interface**: Create a simple command-line interface (CLI) for users to interact with the application.
2. **Bug Reporting**: Implement functionality that allows users to report bugs by providing details such as error messages, steps to reproduce, and any relevant context.
3. **Artifact Collection**: Utilize 'agent-cooking-cli' to automatically collect relevant artifacts from the user's environment when a bug is reported. Artifacts could include logs, system information, and configuration files.
4. **Evidence Analysis**: The application should analyze the collected evidence to identify potential causes of the bug. This could involve pattern matching, keyword searches, or even basic machine learning models if necessary.
5. **Priority Classification**: Based on the severity and impact of the bug, classify it into different priority levels (e.g., critical, high, medium, low).
6. **Bug Tracking**: Integrate with popular bug tracking systems (such as JIRA or GitHub Issues) to automatically create tickets for each reported bug, including all collected artifacts and analysis results.
7. **User Feedback Loop**: Provide feedback to the user regarding the status of their bug report, suggesting possible solutions or workarounds based on the analysis.
8. **Analytics Dashboard**: Develop a basic analytics dashboard within the CLI that shows statistics about recent bug reports, such as the most common issues, frequency of bug reports over time, and resolution times.

How 'agent-cooking-cli' is utilized:
- For Artifact Collection: Use 'agent-cooking-cli' to define which artifacts are essential for bug triage and automate their collection.
- For Evidence Analysis: Leverage the package's capabilities to structure and analyze the collected evidence efficiently.
- For Integration: Utilize 'agent-cooking-cli' to ensure seamless integration between the bug reporting system and external tools or services.

This project not only helps in managing bugs more effectively but also enhances the developer experience by reducing the time spent on manual bug triage.