🤖 AI Analysis

Final verdict: SAFE

Based on the analysis, the package exhibits minimal risks across various categories, with only slight concerns about its metadata indicating potential inactivity or low development effort.

Low network, shell, obfuscation, and credential risks
Metadata suggests possible inactivity but does not indicate malicious intent

Per-check LLM notes

Network: The observed network patterns are typical for packages that require HTTP/HTTPS requests, indicating legitimate API interactions or web service calls.
Shell: No shell execution patterns were detected, suggesting no direct system command execution risk.
Obfuscation: No obfuscation patterns detected, suggesting low risk of malicious activity.
Credentials: No credential harvesting patterns detected, indicating safe handling of sensitive information.
Metadata: The package shows signs of low effort and may be new or inactive, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (4.8/10)

✦ High Test Suite 9.0

Test suite present — 11 test file(s) found

Test runner config found: pyproject.toml
11 test file(s) detected (e.g. test_context_memrez.py)

◈ Medium Documentation 5.0

Some documentation present

Detailed PyPI description (5489 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 7.0

Partial type annotation coverage

Type checker (mypy / pyright / pytype) referenced in project
369 type-annotated function signatures detected in source

○ Low Multiple Contributors 1.0

Unable to verify contributor count: no GitHub repository found

No GitHub repository linked — contributor count unavailable

🔬 Heuristic Checks

⚠ Outbound Network Calls score 7.5

Found 5 network call pattern(s)

self._client = http_client or httpx.Client(timeout=timeout) self._owns_client = http_client is
self._client = http_client or httpx.AsyncClient(timeout=timeout) self._owns_client = http_client is
e client = http_client or httpx.AsyncClient() try: response = await client.request(method, u
e client = http_client or httpx.AsyncClient() try: response = await client.post(
er.test", http_client=httpx.Client(transport=httpx.MockTransport(handler)), ) result =

✓ 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

No GitHub repository linked

No GitHub repository link found

⚠ Maintainer History score 6.0

3 maintainer concern(s) found

Only one version has ever been released — brand new package
Author "Agntz" 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 agntz

Create a mini-application called 'AgntzTaskManager' using the Python package 'agntz'. This application will serve as a task management tool that integrates seamlessly with the Agntz platform, allowing users to manage their tasks more efficiently. Here’s a detailed breakdown of what the application should accomplish:

1. **User Authentication**: Implement user authentication functionality where users can sign up, log in, and securely manage their credentials.
2. **Task Creation**: Allow users to create new tasks, specifying details such as task name, description, due date, priority level, and any relevant tags.
3. **Task Management**: Provide features for editing and deleting existing tasks. Users should also be able to mark tasks as completed.
4. **Task Filtering**: Integrate filtering options based on tags, priority levels, and completion status so that users can easily find specific tasks.
5. **Integration with Agntz**: Utilize the 'agntz' package to connect with the Agntz API, ensuring real-time synchronization of tasks between the application and the Agntz platform.
6. **Notifications**: Implement a notification system that alerts users via email or SMS when a task is due or marked as completed.
7. **Reporting**: Develop a reporting feature that generates summaries of completed tasks and upcoming deadlines.

**Utilization of 'agntz' Package**:
- Use the 'agntz' package to authenticate users and manage sessions.
- Leverage the package's task management APIs to create, read, update, and delete tasks.
- Ensure that all task-related operations are synced in real-time with the Agntz server.
- Use the 'agntz' package to handle notifications and ensure they are delivered through the appropriate channels.
- Integrate the reporting functionalities provided by the 'agntz' package to generate comprehensive reports.

This project aims to showcase the capabilities of the 'agntz' package while providing a practical solution for task management.