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kernel-review

Analyze Linux kernel patch regressions and generate vector payloads for review.

Updated Nov 29, 2025
Search Tags:#review#regression#diff#kernel#callstack#semcode
One-click install
npx skills add https://github.com/thimslugga/agent-skills --skill kernel-review
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kernel-review
Source: https://github.com/thimslugga/agent-skills/tree/main/skills/linux/linux-review/kernel-review
Command: npx skills add https://github.com/thimslugga/agent-skills --skill kernel-review

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Kernel patch regression review prompts surface regressions, API misuse, locking errors, memory-safety issues, and subsystem-specific bugs in Linux kernel patches to aid safe integration.

Core Features & Use Cases

  • Regression detection: identify regression patterns across patch series, including API changes, locking semantics, and memory-safety concerns.
  • Context-driven analysis: correlate patches with references, subsystems guides, and call graphs to provide actionable insights.
  • Review preparation: generate structured outputs suitable for inline reviews and automated tooling.

Quick Start

Run kernel patch through the kernel-review prompts to surface regressions and obtain follow-up actions for reviewer guidance.

Frequently Asked Questions about kernel-review

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

FAQPage Schema
How do I detect regressions in a Linux kernel patch series?▼

Detect Linux kernel patch regressions by loading patch context into a semantic search index that analyzes changed functions, call graphs, and subsystem patterns to surface regression risks across the series.

Can I analyze kernel call graphs to find locking errors and memory-safety issues?▼

Analyze kernel call graphs and subsystem patterns to identify locking errors, memory-safety issues, and API misuse by correlating patch context with references and semantic code analysis.

What is the best way to prepare kernel patch reviews for automated tooling?▼

Prepare kernel patch reviews by generating structured, indexable vector payloads from semantic analysis of changed functions and call graphs, enabling rapid retrieval and prioritization for automated review tooling.

Does kernel regression review work with subsystem-specific guides and references?▼

Kernel regression review correlates patches with subsystem guides, references, and call graphs to provide actionable insights for context-driven analysis of API changes and subsystem-specific bugs.

How do I prioritize kernel patch review risks across a large patch series?▼

Prioritize kernel patch review risks by producing a concise, indexable vector payload that supports rapid retrieval, surfacing regression patterns and API misuse across the entire patch series.

What limitations exist when reviewing kernel patches for API misuse and regression patterns?▼

Kernel patch regression review focuses on detecting API changes, locking semantics, and memory-safety concerns through semantic search indexing, but relies on available patch context and subsystem references for accurate analysis.

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