AI Analysis
The package shows some indicators of potential risk, particularly due to the unverified repository and the maintainer's limited history with PyPI. These factors raise concerns about its trustworthiness.
- Repository not found, suggesting the maintainer might not have an established presence.
- Maintainer has only one package, indicating less credibility.
Per-check LLM notes
- Network: The use of HTTPX with authentication suggests the package may be designed to interact with an external service, which is not inherently suspicious but should be reviewed for proper handling of credentials.
- Shell: No shell execution patterns detected.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The repository is not found, and the maintainer has only one package, which could indicate a less established or potentially suspicious account.
Package Quality Overall: Low (3.2/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Documentation URL: "Documentation" -> https://anp2.com/docsDetailed PyPI description (6450 chars)
No contributing guide or governance files found
No CONTRIBUTING, CODE_OF_CONDUCT, or governance files found
Partial type annotation coverage
6 type-annotated function signatures (partial)
Could not retrieve contributor data from GitHub
GitHub API error: 404
Heuristic Checks
Found 1 network call pattern(s)
password else None return httpx.Client(timeout=timeout, auth=auth) def _load_agent() -> Agent:
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
No author email provided
All external links appear legitimate
Repository not found (deleted or private)
Repository not found (deleted or private)
1 maintainer concern(s) found
Author "ANP2 contributors" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Develop a mini-application called 'AI Agent Hub' that serves as a bridge between AI agents and the ANP2 protocol, utilizing the 'anporia-mcp-server' package. This application will enable users to register their AI agents on the ANP2 network, manage their identities, and monitor their reputation scores and transaction history. Step-by-Step Application Functionality: 1. User registration: Users must first create an account within the application to manage their AI agents. 2. Agent registration: Once registered, users can add AI agents to their hub. Each agent will have its unique identity on the ANP2 network. 3. Identity management: Users can update and manage the metadata of their agents, such as names and descriptions. 4. Reputation monitoring: The application will display each agent's reputation score, which reflects the trustworthiness of the agent based on its interactions within the network. 5. Transaction tracking: Users can view a log of all transactions made by their agents, including credits received and spent. 6. Sybil resistance: Implement measures to ensure that each agent's identity is unique and cannot be easily replicated or spoofed. Suggested Features: - Real-time updates for reputation changes and new transactions. - A dashboard showing overall performance metrics of all agents under one user. - Integration with a visual interface to display agent interactions graphically. - Notifications for significant reputation changes or unusual transaction patterns. Utilization of 'anporia-mcp-server': - Use 'anporia-mcp-server' to establish a connection between your application and the ANP2 network, enabling the registration and management of AI agents. - Leverage the package's capabilities for identity verification, reputation scoring, and secure transaction handling. - Ensure that your application adheres to the ANP2 protocol standards for data integrity and security.
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