code-review-graph-review

Name: code-review-graph-review
Availability: InStock
Author: AniTrend

Detect code changes and analyze impact radius for pull request reviews.

51|6|Updated Mar 10, 2019

Search Tags:#code review #pull request #impact analysis #software quality #test coverage #risk assessment #graph-based tracing

Ready to run

npx skills add https://github.com/AniTrend/anitrend-v2 --skill code-review-graph-review

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: code-review-graph-review
Source: https://github.com/AniTrend/anitrend-v2/tree/main/.agents/skills/code-review-graph-review
Command: npx skills add https://github.com/AniTrend/anitrend-v2 --skill code-review-graph-review

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It eliminates slow, error-prone code review by using change detection and impact analysis to focus attention on the highest-risk areas first.

Core Features & Use Cases

Risk-aware change detection: Identifies and scores what changed and how risky it is, so reviewers don’t miss critical effects.
Affected flow tracing: Finds impacted execution paths and functions rather than relying on manual caller tracing.
Coverage and blast-radius guidance: Checks for tests tied to high-risk functions and proposes concrete test cases for untested changes.

Use case: When reviewing a pull request, you can quickly understand what parts of the system are likely affected, whether existing tests cover the risk, and what targeted tests to add before merging.

Quick Start

Ask the AI to review the PR changes using code-review-graph change detection and impact analysis for a risk-aware merge recommendation.

Frequently Asked Questions about code-review-graph-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I perform a risk-aware code review for a pull request?▼

Risk-aware code review uses change detection and impact analysis to identify and score risky modifications in a pull request. It traces affected execution paths and checks test coverage to focus attention on high-risk areas before merging.

What is the best way to find the blast radius of code changes in a branch diff?▼

Finding the blast radius of code changes requires graph-based tracing to identify impacted execution flows and functions. It calculates the impact radius automatically, replacing manual caller tracing to determine exactly what downstream logic is affected.

How does graph-based impact analysis determine which tests are needed for untested changes?▼

Graph-based impact analysis queries the code graph for tests tied to high-risk functions affected by a pull request. It checks existing test coverage and proposes targeted, specific test cases for any untested changes detected during the review.

Can I review pull request risks quickly without providing extensive manual context?▼

Reviewing pull request risks requires minimal context to start. The process automatically detects changes, queries affected flows, and computes the impact radius using graph-based tracing to deliver a merge recommendation efficiently.

What are the limitations of relying on manual caller tracing during pull request reviews?▼

Manual caller tracing during pull request reviews is slow and error-prone, often missing critical effects. Graph-based impact analysis overcomes this by automatically finding impacted execution paths and assessing risk scores for high-risk functions.

When do I need impact analysis for software quality assurance?▼

Impact analysis for software quality is needed when reviewing branch diffs where the impact radius and affected flows must be determined quickly. It ensures high-risk functions have test coverage and suggests specific test cases before merging.