🤖 AI Analysis

Final verdict: SUSPICIOUS

The package exhibits moderate risks due to potential obfuscation techniques and incomplete metadata, which may obscure its true intentions.

High obfuscation risk
Incomplete author metadata

Per-check LLM notes

Network: The use of an AsyncClient suggests the package performs network requests, which is not inherently suspicious but should be reviewed for context and purpose.
Shell: No shell execution patterns detected.
Obfuscation: The code appears to be obfuscated through partial function calls and comments which could hide the true functionality, raising suspicion.
Credentials: No clear patterns of credential harvesting are evident from the provided snippets.
Metadata: The author's information is incomplete and the account seems new or inactive, raising some suspicion but not conclusive evidence of malice.

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

self._owned_client = httpx.AsyncClient() return self._owned_client async def __aenter_

⚠ Code Obfuscation score 10.0

Found 5 obfuscation pattern(s)

de: return engine.eval(value[1:]) return engine.eval(value[1:], symbols={"E
ue[1:]) return engine.eval(value[1:], symbols={"Env": dict(os.environ)}) except Exc
powerfx` library only exposes eval() with runtime symbols, not the full RecalcEngine API. We wo
t at path '{path}'") def eval(self, expression: str) -> Any: """Evaluate a PowerFx
return engine.eval(formula, symbols=symbols, locale=_POWERFX_EVAL_LOCALE)

✓ 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: microsoft.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository microsoft/agent-framework appears legitimate

⚠ Maintainer History score 4.0

2 maintainer concern(s) found

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-framework-declarative

Develop a simple yet engaging mini-application using the 'agent-framework-declarative' Python package that allows users to manage a virtual library of books. This application will serve as a basic demonstration of how declarative specifications can streamline the creation and management of agents within a system. Here’s a detailed outline of what your application should include:

1. **Application Overview**: Your application will allow users to create, modify, and delete entries for books in their personal digital library. Additionally, it will provide functionalities to search for specific books based on criteria such as title, author, or publication year.
2. **Agent Specifications**: Utilize the 'agent-framework-declarative' package to define agents responsible for different operations within the library system. For example, you might have an agent dedicated to adding new book entries, another for updating existing ones, and yet another for searching through the database.
3. **Features**:
- **Add Book Entry**: Users should be able to input details about a book (title, author, publication year, etc.) and add it to the library.
- **Update Book Information**: Provide functionality to edit any information related to a book entry.
- **Delete Book Entry**: Allow users to remove unwanted entries from the library.
- **Search Functionality**: Implement a search feature that enables users to find books by specifying certain attributes.
4. **User Interface**: Design a user-friendly interface that makes it easy for users to interact with the library system. This could be a command-line interface (CLI) or a simple web-based interface depending on your preference.
5. **Database Management**: Use a local SQLite database to store all book entries. Ensure that data persistence is handled correctly so that changes made by agents are saved and accessible across sessions.
6. **Documentation**: Include comprehensive documentation explaining how each agent works and how they interact with the database. This will help other developers understand and possibly extend your application.
7. **Testing**: Write unit tests for your agents and integration tests to ensure that interactions between agents and the database work as expected.
8. **Deployment**: If applicable, consider deploying your application to a platform like Heroku or Docker for others to try out.

By following these steps, you'll not only demonstrate the power of declarative specifications in managing complex systems but also create a useful tool for managing a personal digital library.