Skills vs Tools vs Rules vs MCP Tools: Hands-On with Langchain, AWS Bedrock Nova

The provided code defines a set of tools that can be used to analyze Python source code. These tools are decorated with @tool, indicating they are meant to be invoked as part of an automated analysis or review process, possibly within a larger system like a linter or static code analyzer.

Here's a breakdown of what each tool does:

1. check_imports: This function checks if the given Python source code imports any modules from os, sys, or subprocess. It returns a message indicating whether these potentially risky imports are present and on which lines they occur.

2. detect_logging: This function looks for logging statements in the provided Python code to ensure that proper logging is being used throughout the application. If it finds any, it will return a positive confirmation along with the line numbers where logging occurs; otherwise, it indicates no logging was found.

3. find_sql_injection_vulnerabilities: This function scans through SQL queries embedded in Python strings to identify potential SQL injection vulnerabilities by looking for placeholders or dynamic content within these strings that could be manipulated maliciously.

4. inspect_code_quality: This tool performs a basic inspection of the code quality, checking for common issues

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