AI Analysis
The package shows minimal risks across all assessed categories with no detected network calls, shell executions, obfuscations, or credential harvesting attempts. The metadata risk slightly increases due to the maintainer having only one package, but overall, there are no clear indications of a supply-chain attack.
- No network calls detected
- No shell execution detected
Per-check LLM notes
- Network: No network calls detected, which is normal unless the package requires external services.
- Shell: No shell execution detected, indicating the package does not execute system commands.
- Obfuscation: No obfuscation patterns detected, indicating low risk.
- Credentials: No credential harvesting patterns detected, indicating low risk.
- Metadata: The maintainer has only one package, which might indicate a new or less active account, but no other red flags were found.
Package Quality Overall: Low (4.2/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Documentation URL: "Documentation" -> https://myaibrain.org/docsDetailed PyPI description (20046 chars)
No contributing guide or governance files found
Development Status classifier >= Beta
No type annotations detected
No type annotations, py.typed marker, or stub files detected
Active multi-contributor project
3 unique contributor(s) across 15 commits in sindecker/aibrainSmall but multi-author team (3–4 contributors)
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: gmail.com>
All external links appear legitimate
Repository sindecker/aibrain appears legitimate
1 maintainer concern(s) found
Author "Matthew McKee" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a personal knowledge management assistant using the 'aibrain' Python package. This assistant will help users manage their notes, documents, and information by leveraging advanced AI capabilities such as memory storage, team collaboration, workflow automation, and continuous learning through document ingestion. The application should allow users to: 1. **Ingest Documents**: Users should be able to upload various types of documents (PDFs, Word documents, etc.) into the system. The AI agent will parse these documents and store relevant information in its memory. 2. **Query Information**: Users can ask questions about the ingested documents or any previously stored information. The AI agent should be able to retrieve and summarize the requested data accurately. 3. **Team Collaboration**: Support multiple users within a single team. Each team member can contribute documents and queries, and the AI agent should consolidate and share insights across the team. 4. **Workflow Automation**: Implement basic workflows where the AI agent can perform tasks like sending reminders, generating summaries, or even initiating actions based on predefined triggers. 5. **Continuous Learning**: The AI agent should continuously improve its understanding of the documents and queries over time, adapting to new information and user preferences. To achieve these functionalities, utilize the core features of the 'aibrain' package such as memory management, team coordination, workflow definition, and continuous learning mechanisms. Additionally, consider integrating a user-friendly interface (web or desktop application) for easy interaction with the AI agent.