agent-collab

v0.1.0 suspicious
4.0
Medium Risk

A general-purpose coordination protocol and CLI for multiple AI coding agents working on one repository.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low risks in direct execution and network activities but raises concerns due to high metadata risk from recent rapid commits and minimal repository engagement.

  • High metadata risk
  • Lack of maintainer history
Per-check LLM notes
  • Network: No network calls detected, which is normal and indicates no immediate risk from network activity.
  • Shell: The shell execution appears to be benign, likely used for version control operations like fetching the project's root directory.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent related to code obfuscation.
  • Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.
  • Metadata: High risk due to recent and rapid commits, lack of maintainer history, and minimal repository engagement.

🔬 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)

  • e() try: result = subprocess.run( ["git", "rev-parse", "--show-toplevel"],
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: outlook.com.tr>

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 5.0

Git history flags: Repository has zero stars and zero forks

  • Repository has zero stars and zero forks
  • All 10 commits happened within 24 hours
⚠ Maintainer History score 6.0

3 maintainer concern(s) found

  • Only one version has ever been released — brand new package
  • 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-collab 
Create a collaborative code review tool using the 'agent-collab' Python package. This tool will allow multiple AI coding agents to work together on reviewing a single codebase, providing feedback, suggestions, and even proposing code changes. The application should have the following features:

1. **Agent Integration**: Integrate at least three different AI coding agents (e.g., CodeReviewerAI, SyntaxCheckerAI, SecurityScannerAI) into the system. Each agent should have a specific role in the review process.
2. **Repository Management**: The tool should support multiple repositories and allow users to specify which repository to review.
3. **Collaborative Review Process**: Implement a workflow where each agent performs its designated task on the codebase and then passes it to the next agent in line. For example, after CodeReviewerAI provides comments, SyntaxCheckerAI checks for syntax errors, and finally, SecurityScannerAI scans for security vulnerabilities.
4. **Feedback Generation**: After all agents have reviewed the code, compile their findings into a comprehensive report that includes comments, suggested fixes, and any flagged issues.
5. **Code Proposal**: If appropriate, based on the feedback from the agents, generate a set of proposed code changes that could address identified issues.
6. **CLI Interface**: Provide a command-line interface (CLI) that allows users to easily manage repositories, start the review process, and view reports.
7. **Configuration Flexibility**: Allow users to configure which agents participate in the review process and customize the order in which they operate.
8. **Logging and Auditing**: Keep a log of all actions performed during the review process, including the time stamps, actions taken by each agent, and any decisions made.

To achieve these functionalities, utilize the 'agent-collab' package to handle the coordination between the different agents. Specifically, use its CLI capabilities to manage the interaction between the agents and the codebase, and leverage its protocol for defining and executing the collaborative workflow among the agents. Additionally, consider extending the functionality of 'agent-collab' if necessary to better suit your application's needs.