Proof of Usefulness Report

llms-txt-gen

Analysis completed on 5/22/2026

+59.4

Proof of Usefulness Score

You're In Business

The llms-txt-gen project addresses a highly relevant and rapidly emerging problem: AI crawler visibility for client-side rendered websites. The CLI tool offers strong real-world utility by automating AI readiness scoring and generating an llms.txt file. However, as an early-stage open-source tool with minimal reported traction (2 GitHub stars) and no established user base or revenue, it scores appropriately in the 'minimal traction' calibration bracket. Market timing is excellent, providing a solid foundation for future growth.

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Score Breakdown

Real World Utility+20

Audience Reach Impact+2

Technical Innovation+10.5

Evidence Of Traction+3.75

Market Timing Relevance+13.5

Functional Completeness+4.25

Subtotal+54

Usefulness Multiplierx1.1

Final Score+59

Project Details

Project URL

github.com/korixinc/llms-txt-gen

Description

An open-source CLI that scores how AI-ready any website is (0–100), flags pages invisible to AI crawlers, and generates a ready-to-commit llms.txt — in one command, no API key. AI assistants and LLM-powered search decide what a site is by reading it; llms-txt-gen gives developers an LLM-Readiness Score, detects client-side-rendered pages AI crawlers see as empty, and writes the llms.txt file from the sitemap automatically.

Audience Reach

Published article on HackerNoon (live, indexed): https://hackernoon.com/llms-txt-gen-earns-a-4978-proof-of-usefulness-score-by-building-an-ai-readiness-cli-tool — part of the #proof-of-usefulness-hackathon tag. Public GitHub repo: https://github.com/korixinc/llms-txt-gen (2 GitHub stars, MIT license, v0.3.0). Tool is runnable today via npx with zero install. Targeting developers, DevOps engineers, and SEO/content teams who manage public-facing websites with AI-crawler visibility risk.

Target Users

Web developers, DevOps engineers, and content/SEO teams who want to ensure their sites are readable and properly indexed by AI assistants and LLM-powered search engines. Anyone publishing a site that uses client-side JavaScript rendering is at risk of being invisible to AI crawlers.

Technologies

Bright Data, Other, Node.js 18+ (zero runtime dependencies), native fetch API, regex-based sitemap parser, Bright Data Web Unlocker (opt-in integration via --bright-data-token flag for JS-heavy/protected sites)

Traction Evidence

Published HackerNoon article (live): https://hackernoon.com/llms-txt-gen-earns-a-4978-proof-of-usefulness-score-by-building-an-ai-readiness-cli-tool GitHub repo (public, MIT, v0.3.0): https://github.com/korixinc/llms-txt-gen Test report (30 tests incl. SSRF + payload-cap): https://github.com/korixinc/llms-txt-gen/blob/main/TEST_REPORT.md Bright Data Web Unlocker integration (opt-in, documented): https://github.com/korixinc/llms-txt-gen/blob/main/README.md KORIX company site (author): https://korixinc.com

Algorithm Insights

Market Position

Growing utility with room for optimization

User Engagement

Documented reach suggests active user community

Technical Stack

Modern tech stack aligned with sponsor technologies

Recommendations to Increase Usefulness Score

Document User Growth

Provide specific metrics on user acquisition and retention rates

Showcase Revenue Model

Detail sustainable monetization strategy and current revenue streams

Expand Evidence Base

Include testimonials, case studies, and third-party validation

Technical Roadmap

Share development milestones and feature completion timeline