🤖 AI Analysis

Final verdict: SAFE

The package appears safe with minimal risks identified. It does not make network calls and has no evidence of obfuscation or credential harvesting.

No network calls detected.
No obfuscation or credential harvesting.

Per-check LLM notes

Network: No network calls detected, which is normal and not indicative of malicious activity.
Shell: Shell execution is used to run 'mkdocs build', likely for documentation purposes, which is expected for development tools but should be monitored for any unexpected commands.
Obfuscation: No obfuscation patterns detected, indicating low risk.
Credentials: No credential harvesting patterns detected, indicating low risk.
Metadata: The package shows low effort and may indicate an inactive or new maintainer, but there are no clear signs 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)

build(self) -> None: subprocess.run( [sys.executable, "-m", "mkdocs", "build", "-f",

✓ 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 sidmitra/agent-archive appears legitimate

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Author name is missing or very short
Author "" 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-archive

Create a mini-application called 'Agentic Explorer' that leverages the 'agent-archive' package to archive and explore past agentic coding sessions. Your task is to develop a user-friendly interface where users can save their coding sessions, retrieve them later, and interactively browse through them. Here’s a detailed breakdown of what your application should achieve:

1. **Session Archiving**: Integrate 'agent-archive' to automatically save each coding session as it happens. Each session should include all the code written, comments made, and any outputs or errors encountered.
2. **Search Functionality**: Implement a search feature that allows users to find specific sessions based on keywords, dates, or even specific lines of code.
3. **Interactive Browsing**: Enable users to navigate through archived sessions, allowing them to scroll through the session timeline, view code snippets, and re-execute parts of the session if necessary.
4. **Session Management**: Provide tools for managing sessions such as renaming, deleting, and organizing into folders or categories.
5. **Collaboration Features**: Optionally, add features that allow users to share sessions with others, either publicly or privately, and collaborate in real-time on code.
6. **Visualization Tools**: Include basic visualization tools to help users understand patterns in their coding behavior over time, such as graphs showing frequency of certain commands or types of errors.

Your application should demonstrate proficiency in utilizing the 'agent-archive' package's capabilities while also showcasing your ability to create a functional and engaging user experience.