Can it analyze uncommitted local changes?

Absolutely. It can run a diff on your current uncommitted changes, specific branches (like main...HEAD), or even specific pull request numbers.

What does the 'blast radius' analysis include?

It identifies '1-hop' connections, meaning any component that directly imports, calls, or depends on the specific code you have modified.

How is the risk assessment calculated?

Risk is assessed by evaluating the complexity scores of the modified nodes, the total number of affected dependencies, and whether the changes bridge multiple architectural layers.

How do I see the results visually?

After running /understand-diff, the skill updates a local JSON overlay which you can then view using the /understand-dashboard command.

Do I need to run /understand before using /understand-diff?

Yes, this skill relies on the knowledge graph generated by the /understand command to map your code changes to the project's architecture.

Understand Diff

Name: Understand Diff
Author: Lum1104

byLum1104

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12,609

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Herramientas de Colaboración

Analyzes Git diffs and pull requests against a project knowledge graph to identify impact zones and architectural risks.

The understand-diff skill bridges the gap between raw code changes and high-level architectural understanding by mapping Git diffs onto an interactive knowledge graph. It automatically identifies which specific components, functions, and classes are modified, then traverses dependency chains to reveal the 'blast radius'—the upstream callers and downstream dependencies potentially affected by the changes. This allows developers and reviewers to perform data-driven risk assessments based on code complexity and architectural layer violations, ensuring that side effects are caught long before code reaches production.

Características Principales

01Visual dashboard integration via automatic diff-overlay generation

0212,609 GitHub stars

03Automated blast radius analysis for changed files and functions

04Dependency mapping to identify upstream callers and downstream side-effects

05Quantitative risk assessment based on code complexity and connectivity

06Architectural layer validation to track cross-layer concerns

Casos de Uso

01Conducting deep code reviews by identifying hidden dependencies affected by a PR

02Visualizing the scope of changes when switching between feature branches

03Assessing the stability risk of refactoring complex legacy components

Características Principales

01Visual dashboard integration via automatic diff-overlay generation

0212,609 GitHub stars

03Automated blast radius analysis for changed files and functions

04Dependency mapping to identify upstream callers and downstream side-effects

05Quantitative risk assessment based on code complexity and connectivity

06Architectural layer validation to track cross-layer concerns

Casos de Uso

01Conducting deep code reviews by identifying hidden dependencies affected by a PR

02Visualizing the scope of changes when switching between feature branches

03Assessing the stability risk of refactoring complex legacy components