AI Analysis
Final verdict: SUSPICIOUS
The package has legitimate purposes but shows signs of potential misuse due to low maintainer activity and poor metadata quality.
- Metadata risk is high with low maintainer activity and poor metadata quality.
- Network calls present but legitimacy needs further verification.
Per-check LLM notes
- Network: The presence of network calls is expected if the package requires internet connectivity for its functionality, but further investigation is needed to ensure legitimacy and security.
- Shell: No shell execution patterns detected, which is positive.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The package shows low maintainer activity and poor metadata quality, raising concerns about its legitimacy.
Package Quality Overall: Medium (5.2/10)
✦ High
Test Suite
9.0
Test suite present — 5 test file(s) found
5 test file(s) detected (e.g. test_adapter_lifecycle.py)
◈ Medium
Documentation
5.0
Some documentation present
Detailed PyPI description (21571 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
301 type-annotated function signatures detected in source
◈ Medium
Multiple Contributors
5.0
Limited contributor diversity
1 unique contributor(s) across 23 commits in FutureUnreal/all-in-agentsSingle author but highly active (23 commits)
Heuristic Checks
Outbound Network Calls
score 1.5
Found 1 network call pattern(s)
from e http_client = httpx.AsyncClient( headers=server.headers, timeout=htt
Code Obfuscation
No obfuscation patterns detected
Shell / Subprocess Execution
No shell execution patterns detected
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
score 2.5
Git history flags: Repository has zero stars and zero forks
Repository has zero stars and zero forks
Maintainer History
score 6.0
3 maintainer concern(s) found
Author name is missing or very shortAuthor "" 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 all-in-agents
Create a fully-functional mini-application called 'TaskMaster' using the Python package 'all-in-agents'. TaskMaster is designed to help users manage their daily tasks efficiently by allowing them to add, delete, update, and mark tasks as completed. Additionally, it will feature a simple scheduling system that allows users to set reminders for specific tasks at certain times of the day. Here's a detailed breakdown of the steps and features: 1. **Setup**: Begin by installing 'all-in-agents' and setting up a basic agent environment within your project. 2. **User Interface**: Develop a command-line interface (CLI) where users can interact with TaskMaster. Ensure the CLI is user-friendly and intuitive. 3. **Task Management Features**: - **Add Task**: Users should be able to add new tasks to their task list. - **Delete Task**: Allow users to remove tasks from the list. - **Update Task**: Provide functionality for users to edit existing tasks. - **Mark Completed**: Enable users to mark tasks as completed. 4. **Scheduling System**: Implement a feature that lets users set reminders for tasks at specific times. This could involve integrating with 'all-in-agents' to create agents that monitor time and trigger reminders. 5. **Agent Utilization**: Use 'all-in-agents' to manage the background processes that handle task management and scheduling. For instance, create agents that periodically check for completed tasks or upcoming reminders. 6. **Testing**: Write tests to ensure that each feature works as expected. Pay special attention to edge cases like handling multiple users or concurrent task updates. 7. **Documentation**: Finally, document your code and provide clear instructions on how to install and use TaskMaster. This project aims to demonstrate the versatility and simplicity of 'all-in-agents' while providing a practical tool for managing daily tasks.
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