A sophisticated C++ code review tool combining regex-based static analysis and 3-way parallel AI reviews to ensure memory safety and performance.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cpp-code-review-master
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install cpp-code-review-master using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is C++ Code Review Master?
C++ Code Review Master is a professional-grade integration within the Openclaw Skills ecosystem designed to elevate code quality in C and C++ projects. It moves beyond standard linting by orchestrating a multi-stage review process that includes local static analysis and deep AI-driven reasoning. This skill is specifically tuned to detect complex C++ issues such as dangling references, undefined behavior (UB), and improper RAII implementation. By utilizing specialized sub-agents, it provides developers with a comprehensive audit of their codebase, ensuring compliance with modern standards from C++17 to C++23 while maintaining high performance and security.
C++ Code Review Master Use Cases
- Performing automated Pull Request reviews to catch memory leaks and logical errors.
- Auditing legacy C++ codebases for security vulnerabilities like buffer overflows and pointer arithmetic risks.
- Transitioning projects to modern C++ standards by identifying deprecated features and suggesting constexpr or smart pointer alternatives.
- Optimizing performance by detecting unnecessary object copying and virtual function overhead.
- Ensuring thread safety in concurrent applications by analyzing mutable members and lock granularity.
How C++ Code Review Master Works
- Context Acquisition: The skill identifies the target scope by scanning specific files, directories, or analyzing git diffs to understand the changes made.
- Local Static Pre-check: It runs a suite of regex patterns to instantly flag dangerous patterns like raw new/delete usage and unsafe C-style functions.
- Parallel AI Review: Three independent AI reviewers analyze the code simultaneously, focusing on functionality, performance/memory, and security/best practices respectively.
- Synthesis and Scoring: The individual findings are aggregated into a unified report that includes a quality score across multiple dimensions.
- Automated Remediation: On user command, the skill can automatically apply fixes to resolve identified bugs and style inconsistencies.
C++ Code Review Master Setup
To get started with C++ Code Review Master, ensure you have the necessary Openclaw Skills dependencies installed in your environment:
# Install the required skill components
/skill install cpp code-review-sr iterative-code-review modified-code-review code-review-fix
# Run a review on your current file
/cpp-review
C++ Code Review Master Data Schema & Taxonomy
The skill generates a structured report organizing findings into the following taxonomy:
| Attribute | Description |
|---|---|
| Severity | Classified as High (e.g., Memory Leaks), Medium (UB), or Low (Modernization) |
| Category | Includes Memory, Logic, Performance, Security, and Readability |
| Location | Precise file path and line number for every identified issue |
| Score | A 100-point scale evaluating Memory Safety, Logic, and Best Practices |
| Priority | Fix recommendations categorized from P0 (Must Fix) to P3 (Optional) |
C++ Code Review Master Advanced Features
- Multi-agent orchestration using 3 parallel sub-reviewers for exhaustive coverage.
- Full support for modern C++ guidelines including C++20 Concepts and C++23 features.
- Integration with GitHub CLI (gh) for seamless PR status and diff analysis.
- Automated 'Learning Mode' via the --explain flag to help developers understand underlying C++ principles.
- Local-first analysis patterns to ensure code privacy before optional AI processing.
SKILL.md
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