auto-skill-mcp

v1.0.0 suspicious
4.0
Medium Risk

One MCP server that auto-serves skills to agentic coding tools

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows low individual risks but raises concerns due to the suspicious metadata and rapid commit history, suggesting potential issues with the package's origin or legitimacy.

  • Metadata risk at 7/10 due to recent repository creation and rapid commit history.
  • Shell risk at 5/10, particularly concerning on Windows systems.
Per-check LLM notes
  • Network: No network calls detected, which is low risk.
  • Shell: Execution of shell commands on Windows systems could be used for malicious purposes if not properly justified within the package's functionality.
  • Obfuscation: No obfuscation patterns detected, indicating low risk of malicious obfuscation.
  • Credentials: No credential harvesting patterns detected, indicating low risk of malicious activity related to secret management.
  • Metadata: The repository's recent creation and rapid commit history, along with the maintainer's new account status, raise suspicion.

📦 Package Quality Overall: Medium (5.4/10)

✦ High Test Suite 9.0

Test suite present — 3 test file(s) found

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

Some documentation present

  • Detailed PyPI description (3317 chars)
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 7.0

Partial type annotation coverage

  • Type checker (mypy / pyright / pytype) referenced in project
  • 61 type-annotated function signatures detected in source
○ Low Multiple Contributors 2.0

Single-author or unverifiable project

  • 1 unique contributor(s) across 9 commits in RahulRachhoya/auto-skill-mcp
  • Single author with few commits — possibly a personal or throwaway project

🔬 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)

  • .platform == "win32": os.system("") sys.stdout.reconfigure(encoding="utf-8") # type
✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

⚠ Git Repository History score 7.5

Git history flags: Repository created very recently: 3 day(s) ago (2026-06-04T18:08:14Z)

  • Repository created very recently: 3 day(s) ago (2026-06-04T18:08:14Z)
  • Repository has zero stars and zero forks
  • All 9 commits happened within 24 hours
⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Rahul Rachhoya" 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 auto-skill-mcp 
Create a versatile code completion tool called 'AutoSkillCraft' using the Python package 'auto-skill-mcp'. This tool will serve as an intelligent assistant for developers, providing real-time code suggestions and enhancing productivity. Here’s a detailed plan on how to build it:

1. **Setup Environment**: Begin by setting up your development environment with Python and installing the 'auto-skill-mcp' package.
2. **Initialize MCP Server**: Use 'auto-skill-mcp' to initialize a server that can automatically manage and serve various coding skills (e.g., language-specific syntax rules, common coding patterns, etc.) to the tool.
3. **Design User Interface**: Develop a simple yet effective user interface where users can input their code snippets and receive suggestions. Consider integrating a command-line interface (CLI) for simplicity.
4. **Implement Skill Integration**: Utilize 'auto-skill-mcp' to dynamically integrate these skills into the tool. Ensure that the tool can understand context and provide relevant suggestions based on the current code snippet.
5. **Enhance with Additional Features**: To make 'AutoSkillCraft' more useful, add features such as error detection, suggestion ranking based on relevance, and support for multiple programming languages.
6. **Testing and Optimization**: Rigorously test the application across different scenarios to ensure reliability and efficiency. Optimize performance and user experience based on feedback.
7. **Documentation and Deployment**: Write comprehensive documentation explaining how to use 'AutoSkillCraft', including setup instructions and examples. Finally, deploy the tool so others can benefit from it too.

This project leverages 'auto-skill-mcp' to streamline the process of building an intelligent code completion tool, making it easier for developers to enhance their coding speed and accuracy.

💬 Discussion Feed

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