General
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/target
node_modules
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Explore
Find agent skills by outcome
99,444 skills indexed with the new KISS metadata standard.
Showing 24 of 99,444Categories: Data, General, Communication, Creative, Coding & Debugging
General
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*.bin filter=lfs diff=lfs merge=lfs -text
website/** linguist-vendored
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.idea
ci
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changesDir: .changes
unreleasedDir: unreleased
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dist/
lib/
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name: 'AI-based PR Reviewer & Summarizer with Chat Capabilities'
description: 'AI-based PR Reviewer & Summarizer with Chat Capabilities'
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CodeRabbit Pro
This is an old version of [CodeRabbit](http://coderabbit.ai) and is now in the maintenance mode.
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Dependency directory
node_modules
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dist/** -diff linguist-generated=true
generic skill
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dist/
lib/
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comment: false
coverage:
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pr_compliances:
- title: "Consistent Naming Conventions"
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[Version 0.11] - 2023-12-07
- codiumai/pr-agent:0.11
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General
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Security Policy
PR-Agent is an open-source tool to help efficiently review and handle pull requests. Qodo Merge is a paid version of PR-Agent, designed for companies and teams that require additional features and capabilities.
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General
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name: 'Codium PR Agent'
description: 'Summarize, review and suggest improvements for pull requests'
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General
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Contributor Code of Conduct
As contributors and maintainers of this project, and in the interest of fostering an open
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Contributing to PR-Agent
Thank you for your interest in contributing to the PR-Agent project!
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<a href="https://github.com/Codium-ai/pr-agent/commits/main">
<img alt="GitHub" src="https://img.shields.io/github/last-commit/Codium-ai/pr-agent/main?style=for-the-badge" height="20">
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.idea/
.lsp/
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2023-08-03
- Optimized PR diff processing by introducing caching for diff files, reducing the number of API calls.
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Repository Guidelines
- **Do** match the interpreter requirement declared in `pyproject.toml` (Python ≥ 3.12) and install `requirements.txt` plus `requirements-dev.txt` before running tools.
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General
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See https://pre-commit.com for more information
default_language_version:
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.venv/
venv/
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Start Here - Instructor for Beginners
A beginner-friendly introduction to using Instructor for structured outputs from LLMs
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