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Rhesis AI

Official

@rhesis-ai · Germany

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5Public Repos
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2Published Skills

The collaboration layer for AI teams: domain experts annotate and review agent behavior, engineers improve the agent from what they find.

🐙 GitHub ↗🌐 Website ↗
Skills Distribution
DomainDeveloper To...Code Quality Assur.. (50%)Documentation Engi.. (30%)Version Control Go.. (20%)

Agent Skills by Rhesis AI

Showing 2 vetted skills indexed across 1 GitHub repositories.

rhesis-airhesis-ai
386

python-linting

Apply Ruff linting and formatting to Python files before commits.

Official
Basic
rhesis-airhesis-ai
386

sprint-review

Generate a markdown changelog from GitHub pull requests grouped into Features and Fixes.

Official
Intermediate

Frequently Asked Questions About Rhesis AI

FAQPage Schema
What specific tasks does Rhesis AI enable for engineering teams?▼

Rhesis AI enables the enforcement of consistent code formatting through Ruff linting and the generation of structured markdown changelogs. These capabilities ensure that repository commits adhere to defined style standards and that release documentation is automatically derived from pull request history.

Which target personas benefit from these capabilities?▼

These capabilities are designed for software engineers, technical leads, and release managers. The functionality assists teams focused on maintaining high code quality standards and those requiring streamlined, accurate documentation of repository changes for project stakeholders.

What are the prerequisites for implementing these features?▼

Implementation requires a GitHub repository environment where pull requests are utilized for code integration. Users must configure the linting parameters for Ruff and ensure appropriate permissions are granted to the repository to allow for the extraction of pull request metadata for changelog generation.