AI Analysis
The package appears to be legitimate with low risks across various categories. While there are some uncertainties regarding network calls and metadata quality, these do not strongly indicate malicious intent.
- Network calls seem legitimate but require confirmation.
- Low maintenance effort raises concerns but lacks evidence of malicious activity.
Per-check LLM notes
- Network: Network calls are likely for legitimate API interactions, but further code review is needed to confirm the purpose and destination of the requests.
- Shell: No shell execution patterns detected, which is normal and expected.
- Obfuscation: The use of base64 decoding for ciphertext and nonce suggests cryptographic operations rather than obfuscation for malicious purposes.
- Credentials: No patterns indicative of credential harvesting have been detected.
- Metadata: The package shows low maintenance and effort, which could indicate potential issues, but no clear signs of malicious intent.
Package Quality Overall: Low (3.8/10)
Partial test coverage signals detected
Test runner config found: pyproject.toml
Some documentation present
Detailed PyPI description (7358 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
214 type-annotated function signatures detected in source
Unable to verify contributor count: no GitHub repository found
No GitHub repository linked — contributor count unavailable
Heuristic Checks
Found 3 network call pattern(s)
ip("/") try: with httpx.Client(timeout=timeout) as client: r = client.post(f"{b) self._http = httpx.Client( headers={ "Authorization": f"Be/") + "/v1/register" with httpx.Client(timeout=timeout) as client: resp = client.post(url,
Found 5 obfuscation pattern(s)
try: ciphertext = base64.b64decode(blob["ciphertext_b64"]) nonce = base64.b64decode(bloertext_b64"]) nonce = base64.b64decode(blob["nonce_b64"]) except (KeyError, TypeError, ValueErrutf-8"), SEP, base64.b64decode(ciphertext_b64), SEP, base64.b64decode(noncext_b64), SEP, base64.b64decode(nonce_b64), SEP, (kind or "").encode("utf-8"(s: str) -> bytes: return base64.b64decode(s) # ── X25519 keypair ───────────────────────────────────
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
No GitHub repository linked
No GitHub repository link found
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)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Develop a personalized virtual assistant named 'Echo' using the 'agenttool-sdk' package, which leverages AI agents for enhanced user interaction and personalization. This application will serve as a bridge between users and their daily tasks, offering a seamless experience through its core functionalities such as memory management, identity verification, and task execution. ### Project Overview: - **Application Name:** Echo - **Primary Functionality:** Personalized task management and information retrieval. - **Target Users:** Individuals looking to streamline their daily routines. - **Core Features:** - Memory Management: Store and recall user preferences and past interactions. - Identity Verification: Securely verify user identity before performing sensitive actions. - Task Execution: Automate routine tasks like setting reminders, scheduling appointments, and sending messages. - Information Retrieval: Provide quick access to information such as weather updates, news, and stock market data. ### Steps to Develop the Application: 1. **Setup Environment:** Begin by installing Python and setting up a virtual environment. Then, install the 'agenttool-sdk' package using pip. 2. **Initialize Echo:** Create a class named 'Echo' that initializes the AI agent with user-specific configurations and settings. 3. **Memory Management:** Implement methods within the 'Echo' class to store and retrieve user interactions and preferences using the 'agenttool-sdk' package's memory feature. 4. **Identity Verification:** Utilize the 'agenttool-sdk' identity verification tools to ensure secure interactions. This could involve biometric checks or password-based authentication. 5. **Task Execution:** Design functions that allow Echo to perform common tasks such as setting reminders and scheduling events based on user commands. 6. **Information Retrieval:** Integrate Echo with external APIs to fetch real-time information such as weather forecasts and news updates. 7. **User Interface:** Develop a simple command-line interface (CLI) for users to interact with Echo. Consider adding voice recognition capabilities for hands-free operation. 8. **Testing and Deployment:** Test all functionalities of Echo thoroughly to ensure reliability and accuracy. Deploy the application so it can be accessed by users. ### How 'agenttool-sdk' Package is Utilized: - **Memory Management:** Use 'agenttool-sdk' to create and manage a user profile that stores interaction history and preferences. - **Identity Verification:** Leverage the identity verification tools provided by 'agenttool-sdk' to authenticate users securely. - **Task Execution & Information Retrieval:** Although these functionalities primarily rely on external APIs and user inputs, 'agenttool-sdk' helps in managing the context and ensuring that each interaction is meaningful and relevant to the user's needs. Echo aims to provide a unique blend of personalization and security, making daily tasks easier and more enjoyable for users.