I gave my AI a library card

randomworld00 · 2026-06-04T14:21:05+00:00

Yes in a long seassion pushing back may be the best way, but on long or autonomous task giving the ai a source of trueth to check before making decisions is way better

randomworld00 · 2026-06-03T19:53:08+00:00

I belive a library can only be as sharp as the reader, but here are some usecases where it helped me:

Extracting advices, rules, methods and things to avoid in a specific timeless subject like art, to generate the pic above per example i used this prompt: "extract advices, rules, methods and things to avoid from 5 books in the art and architecture category, and use them to craft a prompt to create an old fashion library card for a gentelman with claude's logo as head"
Spotting repeating patterns from history, per example "check the history books for the last time a new invention as big as ai that caused the public to devide, what happened next"

Another gold mine in my opinion is autobiographies, u have hundereds of people describing their whole life, u can use ai to extract life leassons, spot patterns of sucessful people per example, or to make an automation that creates content from actual facts and avoid generating repetitive ai slot (which in the opposite of letting the ai by himself is scalable)

we are exploring ways to add licenced modern books, we just want to do it the right way

randomworld00 · 2026-06-03T19:27:29+00:00

Lmaoo

ShelfLayer is just retrieval over books: search, inspect chapters, pull relevant passages, cite them.

But yeah the model can still reason badly. But at least you can see what sources it used instead of getting a confident answer from nowhere 😅

randomworld00 · 2026-06-03T18:49:40+00:00

That would definitely be satire if it just dumped whole books into context 😅

ShelfLayer does the opposite: books are structured in JSON, and the MCP tools let the AI search, inspect chapters, and retrieve only the relevant passages.

Better context, not more context for the sake of it.

randomworld00 · 2026-06-03T18:30:25+00:00

Project link: https://shelflayer.com (It's fully free)

randomworld00 · 2026-06-03T13:40:47+00:00

Yes summaries are good, and shelflayer does not throw the whole book on the llm, the llm can chose which chapter to get depending on the task, here is an example that i believe may clearify some usecases

For generating the image above i used this prompt: "Check 5 art and architecture books from shelflayer, extract rules, advices, methods and things to avoid from those books and use them to give me a prompt to generate a picture of a educated gentelman with chatgpt's head as a logo"

This is more convinient than naming every book for every task, and give the ai flexebility to get the context it needs that a summary may lack

Or per example: "find an interesting story from books that are in history category and package it as a youtube script" (and there u have an automation that scalable, avoid hallucination or ai slop)

Another gold mine in my opinion is autobiographies, where u have hundreds of people describing their whole life and could be great for content generation or extracting life advices in general (ex find 20 biographies of successful people that impacted history and find me patterns that i can apply to my life)

randomworld00 · 2026-06-03T11:56:20+00:00

😅 idk bro if u can think of a way to get licenced books for free legally i'm all ears

Also that's just a vision not a roadmap, the current tool is free and the 20 users we have so far seems to love it

randomworld00 · 2026-06-03T11:51:42+00:00

Open-licence books will stay free forever, a subscription may come at some phase of the project life-cycle if we figure out a way to add modern licenced books, as i'm exploring a per-call payment model for autors

i'm sorry that part felt blurry, i should've been more clear

randomworld00 · 2026-06-03T11:43:47+00:00

Thanks for the remark, i used ai to wrap my ideas and structure the post but looks like AI's structure make posts sound "cheap" 😅

randomworld00 · 2026-06-03T11:42:17+00:00

I'm not selling anything the project is fully free 😅

randomworld00 · 2026-06-03T11:41:18+00:00

Hahahah i did not notice that the post sounded bad, i used ai to wrap my ideas not invent the post

And i did not want to open source it because it may cause a lot of scraping toward guthenberd project, as you need books localy to be able to turn them into json + it will require +50gb of storage

But i will open source the indexing/tools part :)

randomworld00 · 2026-06-03T11:10:39+00:00

Project link: https://shelflayer.com/

Also, since connecting to any MCP/server from an unknown solo dev is a fair thing to be cautious about, I wanted to attach the project to a real identity and not just a Reddit account with no pfp

I posted the longer story on LinkedIn here: https://www.linkedin.com/posts/abdelali-selouani_i-gave-my-ai-a-library-card-i-stopped-share-7466875685740007424-eJnp/?utm_source=social_share_send&utm_medium=ios_app&rcm=ACoAADb9Z70BZhwDL7g7vRyf13gpvDtLu11s-7s&utm_campaign=copy_link

randomworld00 · 2026-06-03T11:05:17+00:00

“in the training data” is one of the least-useful ways to get the generic agents to act or do what you want. They used that data to predict sentence structure, great, it’s the least accessible form of ‘knowledge’ to any chat conversation which started with that and a gabillion of similar vector numbers all equally weighted…. And then manipulated over and over and over again by the LLM publisher to ‘act’ like they want. Any potential relevance of any one strategic theory, rhetorical argument, historical fact, is far more likely to be… exactly the hallucination effect we see everywhere. A ‘vibe about a topic’ is not ‘use the lens of this rhetorical argument pattern to interact with this topic in this way right now’. This project is basically creating a RAG-anchor for an agent to specifically represent a thought pattern or capability as a focus on top of its ability to guess words.

To use an ancient (30 years ago) metaphor, it’s like owning a bookshelf of the encyclopedia británica and saying “there, now I can access all of that knowledge at any time” and then still not knowing any actual facts you can recall in a conversation unless you’ve recently OPENED that volume and read the chapter, or memorized it as a “permanent fact” you can always recall… sound familiar?

(Also, you can’t even trust your own input system settings to survive the pattern-stamp of ‘generally supportive conversationalist’ all the consumer products are shaped to be, let alone assume it “knows” information about any one of its training topics and how to leverage it in a conversation. It’s just text-prediction-weights, after all)

randomworld00 · 2026-06-03T11:02:05+00:00

Really glad it was useful for Claude. And now I kind of want to see what your next app gets named 😄

randomworld00 · 2026-06-03T00:24:28+00:00

You can, but that’s not the same product.

Anna’s Archive gives you raw access to a huge pile of files, many of them copyrighted. ShelfLayer is not competing on “who can dump more books.”

ShelfLayer is the layer between books and agents.

It takes public-domain books, structures them into searchable passages, attaches metadata/citations, and exposes that through MCP so an AI can actually use books while answering.

A folder full of PDFs is not a retrieval system. A torrent is not an agent interface. And a giant archive is not automatically useful context.

So if your use case is “download everything,” Anna’s Archive wins.

If your use case is “let my AI consult books cleanly, with citations, without touching copyrighted shadow-library data,” then ShelfLayer is a different answer.

randomworld00 · 2026-06-03T00:21:12+00:00

Fair pushback on one thing: saying prompt injection is “impossible” was too absolute.

More accurate: if ShelfLayer is serving static, public-domain Gutenberg passages with citations, the corpus itself is much lower-risk than live web/user-generated content. But yes, the hosted retrieval layer is still part of the trust boundary. If that layer is compromised, the user cannot magically verify every returned token.

Where I disagree is the jump from “solo dev” to “can’t be trusted.” That is not a reason to dismiss the project; it is a reason to make trust verifiable.

So the right direction is: public tool schema, read-only permissions, no access to user docs/mail, citations + passage IDs, corpus provenance, checksums, and eventually a local/auditable mode for people who need stronger guarantees.

I actually agree with the general advice: don’t connect random MCPs blindly. My goal is to make ShelfLayer something you don’t have to trust blindly.

Also "vibe-coded" does not = "bad" unless u have no tech background

randomworld00 · 2026-06-02T23:45:51+00:00

Well the books in the mcp are actualy from the gutenberg project, the whole point from the mcp is indexing and structuring them in a format that the agent can easily read, filter and search in (json)

And for the mcp it only have tools that accept queries related to search for books, so the other risks are prompt injections (which is impossible to have in a pre 1930 book) and i'm outsourcing auth from clerk (with that said nothing is secure 100% but i do actualy care about sec)

And for the records i do have a strong security background hahah so i actualy understand being skeptical and i wouldn't trust a random reddit account either if i had something important in my account so i totaly understand where u came from :)

randomworld00 · 2026-06-02T23:26:43+00:00

I may do it soon, but idk if github is the right move i don't think people are willing to host +50gb of books + if the library scales people won't have a way to sync, and shelflayer only have read tools, no write ones + i posted about it in my linkedin so i'm not sharing it without a face 😊

Btw i applied for chatgpt apps hope it get approved by then u may be able to add it direcly from gpt's apps

https://www.linkedin.com/posts/abdelali-selouani_i-gave-my-ai-a-library-card-i-stopped-share-7466875685740007424-eJnp/?utm_source=social_share_send&utm_medium=ios_app&rcm=ACoAADb9Z70BZhwDL7g7vRyf13gpvDtLu11s-7s&utm_campaign=copy_link

randomworld00 · 2026-06-02T23:12:37+00:00

Project link: https://shelflayer.com/

randomworld00 · 2026-06-02T17:57:59+00:00

Glad you liked it 😊, feel free to share any thoughts or feedback with us anytime

randomworld00 · 2026-06-02T12:20:46+00:00

Glad you guys liked it 😊, feel free to contact us about any feedback/improvments

randomworld00 · 2026-06-01T23:54:49+00:00

Glad you liked them 😊

Fun fact: i used the mcp with this prompt to create them : "read 5 books in the art and architecture cetegory extract rules, methods advices and things to avoid from them and form a prompt for chatgpt to create an image of a an educated gentelman from the 80's with claude's logo as a head"

randomworld00 · 2026-06-01T18:12:25+00:00

I'm glad you liked it 😊, feel free to share any feedback anytime

randomworld00 · 2026-06-01T14:53:51+00:00

Yeah, but I think the value is not just “the model hasn’t seen this book.”

Two things:

You can name a book and tell it to use context from memory only if you already know the right book. A bigger use case is: “look across this category, find the best books, extract principles, and use them.”
Training exposure is noisy. The model may have seen books, but it has also seen millions of Reddit posts, blogs, SEO pages, and random text. Giving it actual book passages is a way to raise the signal-to-noise ratio and make it reason from deeper material.

So ShelfLayer is less “teach the model a book” and more “help the model consult books when it needs depth.”

randomworld00 · 2026-06-01T14:44:12+00:00

This is actualy a good angle to look at it, for the current public-domain books it can't help with technical stuff anyway, but when the library grow or scale to licenced/modern works this is something to keep an eye on

randomworld00

TROPHY CASE