Developer Code Toolkit

Problem

Small projects often contain one-off scripts that need quick checks: complexity analysis, import-cycle detection, SQL formatting, regex debugging, API doc generation, JSON Schema inference, Base64/UUID handling, and cron parsing. Installing separate dependencies for each task can be slower than the analysis itself.

How It Works

The skill exposes these tasks as Python functions using only the standard library. The usual flow is “input text or code snippets → parse → structured output”:
- Static analysis: code_complexity_analyzer, dependency_graph_builder, and code_smell_detector use ast, topological sorting, and rule-based checks to inspect code.
- Text and data utilities: sql_formatter_and_validator, regex_engine_tester, and base64_codec_pipeline handle SQL, regex, and Base64 snippets.
- Docs and inference: api_doc_generator and json_schema_inferrer generate documentation or schemas from signatures, docstrings, and samples.
- Generation and scheduling: uuid_generator_with_strategy and cron_expression_parser create identifiers and parse cron expressions.

Boundaries

It is best for local one-off checks and transformations, not for large-repo scanning, runtime profiling, or strongly typed cross-language analysis; Python-specific items may only handle non-Python code as text.