🤖 AI Analysis

Final verdict: SAFE

The package exhibits minimal risk indicators with no network calls, shell executions, obfuscations, or credential harvesting attempts. The only concern is low maintainer activity, but this alone does not suggest malicious intent.

No network calls
No shell executions
No obfuscation
No credential harvesting
Low maintainer activity

Per-check LLM notes

Network: No network calls detected, which is normal unless the package's functionality requires external communication.
Shell: No shell execution patterns detected, indicating no immediate signs of executing system commands.
Obfuscation: No obfuscation patterns detected, indicating low risk of malicious intent.
Credentials: No credential harvesting patterns detected, suggesting safe handling of sensitive information.
Metadata: The package shows signs of low maintainer activity and effort, but there are no explicit red flags indicating malicious intent.

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ 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

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository myriade-ai/agentlys 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 agentlys

Create a simple task management application using the 'agentlys' package in Python. This application will allow users to create, update, delete, and query tasks. Additionally, the app should support categorization of tasks into different projects or categories, and it should be able to set reminders for upcoming deadlines.

Steps:
1. Set up your Python environment and install the 'agentlys' package.
2. Define a Task class that includes attributes such as title, description, due date, category, and status (e.g., pending, completed).
3. Implement basic CRUD operations (Create, Read, Update, Delete) for tasks using the Task class.
4. Integrate 'agentlys' to turn these operations into AI tools, allowing users to interact with the system via natural language commands.
5. Add functionality to categorize tasks into different projects or categories.
6. Implement a reminder feature that sends notifications for tasks approaching their due dates.
7. Ensure the application has a user-friendly interface for both command-line and interactive AI-based inputs.

Features:
- Create new tasks with titles, descriptions, due dates, categories, and statuses.
- Update existing tasks to change any of the attributes mentioned above.
- Delete tasks based on their unique identifiers.
- Query tasks by title, category, status, or due date range.
- Categorize tasks into multiple projects or categories.
- Set reminders for tasks with upcoming due dates.
- Interact with the system using natural language commands processed through 'agentlys'.

Utilizing 'agentlys':
- Use 'agentlys' to convert the Task class and its associated methods into AI tools. This allows the application to understand and execute commands given in natural language, making the task management process more intuitive and user-friendly.