Kyosei (Grade A) logo

Kyosei (Grade A)Security-tested data-ai skill for Claude AI. Grade A. Code review for PRs or local changes. Covers code quality, dependency updates, performance, test coverage, documentation accuracy, and security. U

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Daniel NikulshynReviewed by Daniel Nikulshyn·Updated July 2026

Overview

Kyosei (Grade A) is a security-tested data-ai skill for Claude AI, designed for comprehensive code reviews. It assesses code quality, dependency updates, performance, test coverage, documentation accuracy, and security. The tool is suitable for reviewing Pull Requests (PRs), checking code quality, and running thorough code evaluations. Kyosei operates by utilizing multiple specialized sub-agents in parallel to provide an all-encompassing review. These sub-agents focus on specific areas such as code quality, dependencies, documentation, performance, security, and tests. The tool can be used in GitHub output mode, where results are posted as inline comments on GitHub PRs, or in local output mode, where results are directly printed to the terminal. It also supports simplified reviews for cases where the changeset between the current and previous review is minimal or empty.

Key features

  • Code quality review
  • Dependency updates assessment
  • Performance evaluation
  • Test coverage analysis
  • Documentation accuracy check
  • Security review

Pricing

Model
Free
Category
Skills
Rating
No reviews yet

Use cases

Code Review for Pull Requests

Use Kyosei to comprehensively review PRs, ensuring code quality, security, and performance standards are met before merging.

Local Code Quality Checks

Run Kyosei locally to evaluate code quality, identify areas for improvement, and ensure adherence to best practices.

Pros & Cons

Pros

  • Comprehensive code review capabilities covering multiple aspects
  • Utilizes specialized sub-agents for in-depth analysis
  • Supports both GitHub and local output modes
  • Can perform simplified reviews for minimal changes

Cons

  • Requires configuration and understanding of its output format
  • Depends on the quality of the sub-agents' prompts and configurations

Battle record

Across 1 battle in the Pantheon.

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1st
1
2nd
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3rd

Last battle

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Q&A

What are the limitations of Kyosei?

Kyosei requires configuration and understanding of its output format, and its effectiveness depends on the quality of the sub-agents' prompts and configurations.

Asked by Larisa Ionescu · Mar 22, 2026

How does Kyosei work?

Kyosei utilizes multiple specialized sub-agents in parallel to provide a comprehensive review, each focusing on a specific area.

Asked by Greta Nowak · Mar 1, 2026

Where can Kyosei post results?

Kyosei can post results as inline comments on GitHub PRs or print them directly to the terminal.

Asked by Ivo Novotný · Feb 11, 2026

What does Kyosei review?

Kyosei reviews code quality, dependency updates, performance, test coverage, documentation accuracy, and security.

Asked by Ismael Rios · Feb 1, 2026

Ask a question

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