Rank ADVPL/TLPP functions by maintainability using McCabe complexity and related metrics.
npx skills add https://github.com/JoniPraia/plugadvpl --skill plugadvpl-metrics
Please help me install this Agent Skill. Skill: /plugadvpl:metrics Source: https://github.com/JoniPraia/plugadvpl/tree/main/skills/metrics Command: npx skills add https://github.com/JoniPraia/plugadvpl --skill plugadvpl-metrics
Ajuda você a identificar quais funções do seu código ADVPL/TLPP estão mais complexas e caras de manter, para saber por onde começar um refactor sem depender de achismos.
cc (1 + decisões por If/ElseIf/While/For/Case/Catch/IIf) para priorizar risco e dificuldade.loc, nesting (profundidade), n_calls_out (fan-out/chamadas) e params_count (quantidade de parâmetros), além de has_doc (presença de header Protheus.doc).Peça para listar as 10 funções mais complexas do projeto: /plugadvpl:metrics --sort cc
High-intent search queries and answers about installing and using this skill.
Rank ADVPL functions by cyclomatic complexity to prioritize refactoring by computing McCabe complexity alongside LOC, nesting depth, fan-out, and parameter count to identify high-maintenance functions. The tool parses decision constructs like If/ElseIf/While/For/Case and outputs sortable lists.
ADVPL metrics needed to identify large functions include lines of code, nesting depth, fan-out calls, parameter count, and header documentation presence. These combined metrics highlight functions with high ramification and low documentation that are prime candidates for decomposition.
Yes, you can calculate code quality metrics for a single .prw file or across a whole ADVPL project. The tool parses function boundaries and caches the computed metrics, allowing you to apply threshold filters to target specific files or scan the entire codebase.
Find the most complex TLPP functions by sorting the computed metrics output by cyclomatic complexity. This automatically ranks functions based on decision constructs and structural factors, eliminating guesswork and highlighting where maintenance risks are highest.
Yes, the ADVPL metrics analysis checks for Protheus.doc header documentation presence. It evaluates the has_doc flag alongside structural metrics like nesting and fan-out to prioritize refactoring efforts on complex functions lacking proper documentation.
The best way to triage ADVPL refactoring targets is by ranking functions using combined metrics including cyclomatic complexity, LOC, and nesting depth. This approach processes the entire project to produce a sortable output with optional threshold filters for targeted triage.
totvsGenerate ProtheusDOC comment blocks for AdvPL and TLPP source code elements.
billwanggithubSimplify complex code into readable, maintainable structures while preserving functionality.
totvsRefactor ADVPL/TLPP code with behavior-preserving, small-step changes.
openshiftMeasure cyclomatic and cognitive complexity in Python code under ols/ and generate a ranked report.