Llms.md – a README.md for LLM-powered coding agents

Hacker News

Hi HN, We just published LLMS.md, an open specification for helping Large Language Models (LLMs) understand code repositories. The idea is simple: • README.md helps humans • robots.txt helps crawlers • LLMS.md helps AI coding agents (Copilot, Cursor, Claude Code, Gemini CLI, etc.) A root-level LLMS.md gives agents: • Key directories & entry points • Which files to ignore (dist, deps) • Run/test instructions • Reasoning hints from maintainers Spec: github.com/llmspec/llms-spec RFC: llmspec/llms-spec/rfc/0001-llms-md-spec.md We’d love feedback, contributors, and early adopters. If you maintain an OSS repo, try adding a LLMS.md and let us know what worked!

Visit product View on Hacker NewsAug 31, 2025

Share card

Actual performance

2points

4comments

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, cursor · Missing: mac, macos, apple

98%98% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released

35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

README.md scaffold for rails apps40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

README.md scaffold for rails apps

Hacker News1

GitHub README.md Previewer41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

GitHub README.md Previewer

Hacker News1

AGENTS.md92%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A README, but for your AI coding agent

Product Hunt+229Open Source

ScoreMe, a score for your project's README.md41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ScoreMe, a score for your project's README.md

Hacker News6

GitHub Badges for Profile Readme.md37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

GitHub Badges for Profile Readme.md

Hacker News5

I built a free AI README.md generator33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I built a free AI README.md generator

Hacker News1

Generate README.md files for Go applications35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Generate README.md files for Go applications

Hacker News2

I used the Regions repo to critique its own README.md25%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I used the Regions repo to critique its own README.md

Hacker News2

I create README.md for my machine learning models46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I create README.md for my machine learning models

Hacker News3

Transform and insert your README.md in your static site55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Transform and insert your README.md in your static site

Hacker News2

Browse all products Analyze your launch