amormorri-memory-kernel

v0.2.0 suspicious
4.0
Medium Risk

Focused local memory for AI agents with SQLite FTS5 and deterministic context packing.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low direct risks but has incomplete metadata, indicating potential unreliability.

  • Incomplete author information
  • Single package maintainer
Per-check LLM notes
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity.
  • Credentials: No credential harvesting patterns detected, suggesting the package does not engage in secret or credential theft.
  • Metadata: The author information is incomplete and the maintainer has only one package, which may indicate a less experienced or potentially suspicious user.

📦 Package Quality Overall: Medium (5.4/10)

✦ High Test Suite 9.0

Test suite present — 5 test file(s) found

  • Test runner config found: pyproject.toml
  • 5 test file(s) detected (e.g. test_crud.py)
◈ Medium Documentation 5.0

Some documentation present

  • Detailed PyPI description (13007 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 5.0

Partial type annotation coverage

  • 91 type-annotated function signatures detected in source
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 15 commits in Artem362/memory-kernel
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

⚠ Shell / Subprocess Execution score 2.0

Found 1 shell execution pattern(s)

  • _NATIVE", None) result = subprocess.run( [sys.executable, "-c", BENCH_CODE], cwd=ROO
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: gmail.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository Artem362/memory-kernel 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 amormorri-memory-kernel 
Create a personal knowledge management tool called 'MemoMaster' using the Python package 'amormorri-memory-kernel'. This tool will allow users to store, search, and manage notes efficiently. Here are the steps and features you need to implement:

1. **Setup**: Install the necessary packages including 'amormorri-memory-kernel'.
2. **User Interface**: Develop a simple command-line interface (CLI) for user interaction.
3. **Note Storage**: Implement functionality to add new notes. Each note should include a title and content.
4. **Search Functionality**: Utilize the 'amormorri-memory-kernel' package's SQLite FTS5 capabilities to enable users to search for notes based on keywords found within the titles and contents.
5. **Contextual Search Enhancements**: Enhance search results by leveraging 'amormorri-memory-kernel' to provide more relevant matches based on contextual information packed deterministically into each note entry.
6. **Note Management**: Allow users to delete, update, and view their notes.
7. **Backup & Restore**: Implement a feature to backup all notes to a file and restore them from the same file.
8. **Integration Testing**: Ensure all functionalities work as expected through integration testing.

The 'amormorri-memory-kernel' package is utilized throughout the project to handle the storage and retrieval of notes with enhanced search capabilities. It provides a focused local memory system that supports efficient querying of stored data, making it ideal for applications like 'MemoMaster' where quick access to specific pieces of information is crucial.

💬 Discussion Feed

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