ait-vcs

v1.7.2 safe
3.0
Low Risk

Run Claude Code, Codex, Aider, Gemini CLI, and Cursor as isolated, reviewable attempts with repo-local memory, agent handoff, and apply/recover. MIT, no SaaS.

🤖 AI Analysis

Final verdict: SAFE

The package ait-vcs v1.7.2 presents minimal risks based on the analysis. It has no network calls or obfuscation, and does not pose a threat in terms of credential handling.

  • No network calls
  • Low shell execution risk
  • No obfuscation detected
  • Safe handling of credentials
Per-check LLM notes
  • Network: No network calls detected.
  • Shell: Shell executions are likely related to version control and issue management but could indicate potential for unauthorized actions if misused.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting safe handling of secrets and credentials.
  • Metadata: The maintainer has only one package, suggesting a new or less active account, but no other suspicious flags were raised.

📦 Package Quality Overall: Medium (5.0/10)

◈ Medium Test Suite 6.0

Partial test coverage signals detected

  • Test runner config found: pyproject.toml
◈ Medium Documentation 7.0

Some documentation present

  • Documentation URL: "Documentation" -> https://m24927605.github.io/ait/
  • Detailed PyPI description (8707 chars)
○ Low Contributing Guide 2.0

No contributing guide or governance files found

  • No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • 252 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 5.0

Limited contributor diversity

  • 1 unique contributor(s) across 100 commits in m24927605/ait
  • Single 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 score 10.0

Found 6 shell execution pattern(s)

  • alse) -> str: completed = subprocess.run( ["git", *args], cwd=cwd, check=Fals
  • le[str, ...]: completed = subprocess.run( ["git", "ls-files", "*.md", "docs/*.md"], c
  • -> bool: try: r = subprocess.run( ["gh", "auth", "status"], capture_o
  • urn None try: r = subprocess.run( ["gh", "issue", "create", "--repo"
  • Process[str]: completed = subprocess.run( ["git", *args], cwd=cwd, text=True,
  • try: completed = subprocess.run(command, cwd=workspace, env=env, check=False) exit_c
✓ 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 m24927605/ait appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "michael.chen" 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 ait-vcs 
Create a Python-based mini-application named 'RepoBot' that leverages the 'ait-vcs' package to manage code reviews and version control tasks within a local repository. RepoBot will serve as a versatile tool for developers to perform various operations such as running code analysis, integrating different AI services for code suggestions, and maintaining a history of changes made during development sessions.

### Key Features:
1. **Code Analysis**: Automatically run code analysis tools on any committed changes in the repository.
2. **AI Code Suggestions**: Utilize services like Claude Code, Codex, Aider, Gemini CLI, and Cursor to generate code suggestions based on the current state of the repository.
3. **Version Control**: Implement features to commit, push, pull, and manage branches using 'ait-vcs'.
4. **Review Sessions**: Allow developers to initiate review sessions where they can receive suggestions from integrated AI services and make changes accordingly.
5. **History Tracking**: Keep a record of all changes made during each session, including the suggestions provided by AI services and the final commits.
6. **Agent Handoff**: Enable seamless handoff between different agents (e.g., switching from one AI service to another) without losing context.
7. **Apply/Recover Changes**: Provide functionality to either apply the reviewed changes directly or revert back to the original state before review.

### How 'ait-vcs' Package Will Be Used:
- **Isolated Attempts**: Each review session will be treated as an isolated attempt, ensuring that suggestions and changes are not mixed up between different sessions.
- **Repo-local Memory**: Maintain a local memory of the repository's state during each session, allowing for consistent and accurate analysis and suggestions.
- **Agent Handoff**: Facilitate smooth transitions between different AI services, ensuring that the context and progress are preserved throughout the review process.
- **Apply/Recover**: Implement mechanisms to either apply the reviewed changes permanently or recover to the initial state if needed.

Your task is to design and implement this application using Python, focusing on user-friendly interfaces and efficient integration of the 'ait-vcs' package. Ensure that the application is well-documented and easy to extend with additional features or AI services in the future.