ai-agent-vcr

v0.7.0 suspicious
4.0
Medium Risk

ACID transactions, time-travel debugging, and zero-cost Ghost Replay for AI agents. Rollback filesystem + state. Works with LangGraph, CrewAI, or raw Python.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risks in terms of network calls, obfuscation, and credential handling. However, the shell risk due to Git commands and metadata risk from the missing maintainer's author name and possibly inactive account warrant further investigation.

  • Shell risk due to Git commands
  • Missing maintainer's author name
Per-check LLM notes
  • Network: No network calls detected, indicating low risk of data exfiltration.
  • Shell: Git commands suggest the package is setting up a local Git repository, which may be intended for version control purposes but could potentially be used for unexpected actions.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The maintainer's author name is missing and the account seems new or inactive, which raises some concerns but does not strongly indicate malicious intent.

📦 Package Quality Overall: Medium (7.0/10)

✦ High Test Suite 9.0

Test suite present — 14 test file(s) found

  • Test runner config found: conftest.py
  • Test runner config found: pyproject.toml
  • 14 test file(s) detected (e.g. conftest.py)
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://ixchio.github.io/agent-vcr/
  • Detailed PyPI description (21154 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 243 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 5 unique contributor(s) across 55 commits in ixchio/agent-vcr
  • Active community — 5 or more distinct contributors

🔬 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)

  • DIM}Git history:{RESET}") os.system(f"cd {workspace} && git log --oneline --graph --all 2>/dev/n
  • ".git").exists(): subprocess.run(["git", "init"], cwd=self.workspace_dir, check=True)
  • _dir, check=True) subprocess.run(["git", "config", "user.name", "Agent VCR"], cwd=self.worksp
  • _dir, check=True) subprocess.run(["git", "config", "user.email", "[email protected]"], cwd=self
  • _dir, check=True) subprocess.run(["git", "branch", "-m", "main"], cwd=self.workspace_dir, che
  • init_file.touch() subprocess.run(["git", "add", "-A"], cwd=self.workspace_dir, check=True)
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository ixchio/agent-vcr appears legitimate

⚠ 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 ai-agent-vcr 
Create a Python-based AI agent named 'TimeTravelTutor' that utilizes the 'ai-agent-vcr' package to provide educational content with a twist of time-travel debugging capabilities. The application will allow users to interact with an AI tutor that teaches programming concepts. However, if the user makes a mistake during the tutorial session, they can use the time-travel debugging feature provided by 'ai-agent-vcr' to revert back to a previous state where they made no mistakes, allowing them to learn from their errors without frustration.

The core functionalities of TimeTravelTutor include:
- Interactive lessons on basic Python programming concepts such as loops, conditionals, functions, and data structures.
- A virtual environment that simulates real-world coding scenarios, where users can practice writing code.
- An AI tutor that provides feedback on the user's code and guides them through the learning process.
- A time-travel debugging feature that allows users to roll back to any point in their learning session where they have not made any errors, thanks to the 'ai-agent-vcr' package's ACID transaction support.

The project should also incorporate the following features:
- User authentication and profile management to track progress across multiple sessions.
- Integration with a database to store user interactions and learning outcomes.
- A simple web interface built using Flask or Django for better user experience.

To utilize 'ai-agent-vcr', you'll need to set up an ACID-compliant transactional context for each user session. This ensures that all actions taken within the session are recorded and can be replayed or rolled back if necessary. Additionally, implement a mechanism for users to trigger the rollback functionality when they encounter difficulties, thereby allowing them to start over from a clean slate.

Your task is to design and implement this mini-application, ensuring that it effectively leverages 'ai-agent-vcr' to enhance the learning experience by providing a seamless way to learn from mistakes without the stress of failure.