eli64s/readme-ai

README file generator, powered by AI.

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eli64s/readme-ai has 3k+ stars and 250+ forks on GitHub, is written in Python, and was last pushed on Oct 14, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 10 minutes ago
Added to GitGenius on October 7th, 2026
Created on January 16th, 2023
Open Issues & Pull Requests: 60 (+0)
GitHub issues: Enabled
Number of forks: 296
Total Stargazers: 3,004 (+0)
Total Subscribers: 18 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 11.3 days
Mean response time: 61.7 days
90th percentile: 207.4 days
Tracked items: 29

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Issue Activity (beta)

Open issues: 29
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 579 days
Stale 30+ days: 28
Stale 90+ days: 27

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (4)
  • documentation (2)
  • enhancement (2)
  • feature (2)

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Detailed Description

ReadmeAI is a README file generator powered by AI that automatically creates documentation from a codebase.

The tool solves the problem of manual README creation by processing a repository and using language models to generate structured documentation. A developer provides a URL or path to their codebase, and the tool analyzes the code to produce a well-formatted README file. The approach leverages a repository processing engine combined with advanced language models to understand the project structure and purpose.

ReadmeAI suits developers who want to quickly generate initial documentation without writing it manually. It works well for projects of any size where a standard README structure is appropriate. The tool supports multiple AI providers, allowing users to choose their preferred language model backend. Customization options are available for those who need to tailor the generated output to specific requirements.

The project maintains active development with regular updates and improvements to its core functionality. The codebase shows consistent refinement of the documentation generation pipeline. The tool includes a command-line interface for easy integration into developer workflows. Support for multiple language model providers indicates ongoing effort to keep the tool compatible with evolving AI services.