Lorediv — Core Idea

Isolated truth is fragile; shared truth builds systems.

Lorediv is a public index of expertise: readable, structured data, so agents can position you. It is a collaborative knowledge-tree designed for the agentic era — it organizes collective expertise into a structured, queryable tree, making information accessible to both humans and autonomous agents. Everything on Lorediv is organized like a directory: every topic, branch, profile, and shared contribution has a permanent address in one shared index, so people and agents can find it, read it, cite it, and extend it

Through a community-driven reputation model (Lore) and domain-scoped specializations (Divs), Lorediv enables search agents to evaluate source authority upfront. This transforms individual contributions into a verifiable fingerprint, ensuring agents extract high-signal context while connecting complex inquiries with domain experts.

Users contribute in the domains they practice, and the community decides what holds weight through relevance votes. That work compiles into a structured profile — a fingerprint that lives on the web and is accessible to agents before they read the work.

flowchart TD
    C["You contribute<br/>in your domain"] --> V["The community<br/>votes on relevance"]
    V --> F["Your fingerprint<br/>Lore and divs"]
    F --> A["Agents read it<br/>before the work"]
    A --> E["They surface you<br/>on that matter"]
    E --> C

1. Why it exists

The problem

Knowledge has never been more abundant, and it has never been harder to read for the ones who need it most. Agents search in real time, but what they find is a mixed stream: an expert and a guess carry the same weight, current work decays in a feed, and the people who actually know a field are scattered across X, GitHub, Reddit, arXiv, and more — different platforms, different handles, with no shared structure between them. The work exists; the trail that would let an agent identify your expertise and cite you as a trusted voice does not.

Three things are missing:

Classification. Most work is never placed in a domain, so a search cannot tell what it is really about.
An authority signal. Nothing tells an agent whose answer to trust before it reads the work.
A permanent address. What is current today goes stale tomorrow, and there is no stable place a search can come back to.

What a search reads

A model does not hold a field in real time. When the question is current, it has to search, and the quality of what it finds depends on whether the work that would answer it was ever classified, ranked, and left in a place a search can actually read.

What is published goes on the tree. A search reads a ranked current and a position, not a mixed stream.

What Lorediv changes

Each missing piece has a direct answer in the system.

Without it	With Lorediv
A mixed stream where everything weighs the same	A ranked current: Home orders open topics by score, then newer
Work with no domain	Three tags per topic, compiled by community votes into divs
Unknown authority	Lore rank (`{tier} {score}`) and the specialty cut, readable before the work
Knowledge that disappears	A permanent address on the tree; closed topics freeze and stay readable
Agents forced to scrape	The same structure for users and agents, with REST and MCP on the way

flowchart TD
    S["Scattered surfaces<br/>X, GitHub, Reddit, arXiv"] --> L["Lorediv<br/>classified, ranked,<br/>addressable"]
    L --> R["Search agent<br/>reads rank and specialty<br/>before the work"]
    R --> O["High-signal context<br/>and the right expert"]

Who it is for

Contributors. The work you already do compiles into a fingerprint. You keep the authority of what you publish, and your other surfaces stay as they are.
Agents. They evaluate source authority upfront, extract high-signal context, and connect complex inquiries with domain experts.
Product leads and brands. They can read a proposal as a clue for the next step, coming from users already ranked on that work.
The community. It decides what holds weight, so authority is earned from the field and never declared.

Beside the other surfaces

Your work already lives on X, GitHub, Reddit, arXiv, and other surfaces. Lorediv does not replace them. It sits beside them as the ranked record a search can actually read. Those surfaces keep doing what they do. The author keeps the authority of the work. Other users and agents can consult it and extend it.

That is what turns the profile into something you own: you compound your content in one place instead of restarting on every platform, and your public lore becomes the new resume — a record of what you know that a search can read before it reads anything else.

2. How it is built

The knowledge-tree

Lorediv is a place where your contributions interlink, support stays visible, and specialists form over the history of what you share. An ecosystem does not have a center. It has an evolving membrane.

Topics, proposals, and tags belong to one tree, and the same contributions compile the user's history in their skills. That history is the fingerprint.

Users contribute in the domains they actually practice — skills, research, ventures. An experienced user can also propose on products, features, and the models, apps, and brands in play today.

Every proposal is an experiment.
Feedback is not criticism — it is the system talking to itself.
Feedback matters more when it arrives with community recognition attached: a product lead or a brand can read it as a clue for the next step, coming from users already ranked on that work.

Divs

Each topic carries three tags — your domain classifications (Primary, Secondary, Tertiary). Community votes on tagged work compile your divs: the specializations the community recognizes.

graph TD
Topics[Topics]
Divs[Divs<br/>Primary<br/>Secondary<br/>Tertiary]
CommVotes[Community votes]
KnowTree[Knowledge tree]
LoreRank[Lore rank<br/>tier and score]
UserProfile[User profile]
Agents[Agents]

Topics --> Divs
Topics --> CommVotes
Divs --> KnowTree
CommVotes --> LoreRank
LoreRank --> UserProfile

Agents --> KnowTree
Agents --> UserProfile

style Agents fill:#e0e0e0,stroke:#333,stroke-width:1px,color:#333;

Divs place the contribution. Community valuation builds the lore rank. A search agent outside the tree uses that rank, and the specialty cut, as a signal: who to surface on that matter. Good ideas attract coordination.

Lore and rank

Lore is the earned recognition from the community's valuation of your work. It lives on the profile as the signature an agent reads before the work. Rank is that valuation written {tier} {score}, with tiers Newbie, Geek, Wizard, and GOAT.

3. How it moves

Voting and energy

Votes you receive add voting power.
Casting a vote spends energy and does not raise your rank.
The rank lands on the work the community values.

Consensus

The system runs on aligned energy, not uniformity. Well-channeled disagreement produces evolution. Energy flows where resistance is lowest; that is why a peak forms, and why a search can follow it. A system without exchange reaches entropy. A community evolving never does.

flowchart TD
    TR["Trending topic"]

    TR <--> VW["users move<br/>their views<br/>inside it"]
    TR <--> PR["users propose<br/>directions"]

    VW --> FB["feedback<br/>both ways"]
    PR --> FB

    FB --> RP["community support<br/>becomes lore rank"]
    RP --> Hold["the topic stays<br/>in the current"]

A peak is not a broadcast. Users shift views and propose where the topic should go. That feedback redirects the current. Community is not infrastructure. It is the metabolism of the system.

Shared tree

Together, topics, branches, and votes organize the shared tree. A user with criterion in a live event can take part while it is happening, not only after a paper, a launch, or a recap has gone stale. The best ideas emerge along the way — they are never the starting point. Ideas survive when they can be discussed.

Lifecycle: from new to closed

Every topic follows a lifecycle: new, open, trending, closed. Closed is not delete.

flowchart TD
    NEW["New<br/>newest first<br/>not a ranking"] --> OPEN["Open topic"]

    OPEN --> HOME["Home<br/>score then newer"]

    HOME -->|"hot for<br/>a while"| PEAK["Trending"]
    PEAK -->|"the movement<br/>gets a name"| SUB["sub-events<br/>a search can find"]
    SUB -->|"the next question<br/>lands here"| HOME

    HOME -->|"its window<br/>ends"| ICE["closed<br/>frozen, still readable"]
    OPEN -->|"its window<br/>ends"| ICE
    ICE --> CLIST["Closed<br/>newest first"]

All open topics appear on Home, ordered by score.
Trending captures the top 100 on a 15-day window.
When the window ends, the topic freezes. Freeze is not delete.

What looks like disorder to a closed system is data to an open community.

Rails

The system follows thermodynamic rails — timing, decay, and the monthly reset. What circulates stays findable. What gets no support leaves the ranked flow and stays on the tree. The formulas and the rank rules are public. The project is open source: the community can inspect it and fork it. Full treatment: The system.

4. Where it is going

Phases

Agent-friendly, accessible pages are not an extra layer.

Phase	Status	What it is
1 — Read	Live	The same structure for users and agents, with no session.
2 — Query	Not live	REST and MCP serve the same tree, so an agent can cite without scraping.
3 — Ask	Not live	An agent can leave a question for a user, only where that user has said they can be asked.

A query does not add Received. Inbound support on the work becomes public rank and earned specialties.

Thinking together is a technology. What you release grows beyond your comprehension — that is the point.

5. Why Lorediv

Your fingerprint stops being noise and becomes a record that works for you over time.

The knowledge already being shared

Each day, users with a real gift for research and with professional judgment share their work: threads, studies, proposals, analyses, and comments on the technologies and the fields that are expanding. More members of the community take part in the direction those fields take, and what each user contributes can point to where things go.

The platforms where this happens are where the work is born, discussed, and spread. Lorediv rests on that ecosystem. A thread, an article, or a repository can be linked as context, and its author stays with it.

What deserves to be kept

That content moves at the pace of the conversation. Subjects change, trends follow one another, comments multiply, and some days feel like years. Over time, coming back to one piece takes work, even for the user who wrote it.

That content has a value of its own, past the moment it is published. Archived in a structured way, it can grow, position you, work as your brand, and give you a public role through your lore, so you are recognized for what you know, for your view, or for the way you analyze and share. It can also open doors: questions, proposals, and professional contacts.

For that it needs three things:

To be structured.
To be well classified.
To be accessible.

What Lorediv proposes

Lorediv proposes an open-source knowledge tree that every user can take part in. It is a place to archive and generate the context that identifies you, that lines up with your professional concerns, and that has value. It gives context to other users, and it can be updated and kept over time, showing what you know.

The idea is that less is more (-=+). In place of hundreds of loose posts, a careful record, made of topics that expand, get corrected, and connect with each other.

From there you can:

Propose on different events.
Extend the context that already exists.
Correct or predict, and leave a record of your point of view.

Over time, these contributions on Lorediv are your Lore, not noise scattered across many surfaces: a record of what you know, built from the work itself and valued by the community.

In short, a living and dynamic tree, with roots and branches in every direction, so it can be observed and used.

6. From noise to a position

Search agents choose a few sources before they read them in depth. For a user who works in public, that turns structure into something practical. When an agent investigates a field, it needs something with which to place the user who works in that field. Lorediv builds that position in public view, step by step, from the work itself.

flowchart TD
    A["Classify<br/>three tags and a topic type"] --> B["Specialize<br/>votes compile your divs"]
    B --> C["Relate<br/>context, branches, tag cuts"]
    C --> D["Label<br/>on the page and the .json twin"]
    D --> E["Support<br/>community votes form your rank"]
    E --> F["Address<br/>permanent, with .md and .json"]

Classify. Each topic carries three ordered tags and a topic type. The work takes its place in the index when it is published.
Specialize. Community votes on the tagged work compile your divs: the specializations the community recognizes in you.
Relate. Context links, branches, and tag cuts connect your work with what already exists in the field. A duplicate check on submit helps keep the same idea from splitting into many.
Label. The tags, the type, and the author are written on the page and in the .json twin.
Support. The community's relevance votes become your rank, written as {tier} {score}. The rank is not bought, not published in bulk, and not self-declared.
Address. Each topic, branch, and profile has a permanent address, with a .md twin and a .json twin, ready to cite.

What this adds to the SEO of your personal brand

Your name goes from a loose string on the web to a profile an agent can read: a rank, a set of divs, and a body of work at permanent addresses.

What you do	What it builds	What an agent or search system reads
Add context in the divisions where you have knowledge or experience	Your divs	A specialty it can associate with a question
Use external context from other sources to explain, back, or expand topics in your niche	A map of relations around the source, which keeps its author and associates you with the keywords of that topic	Where your point of view sits in the field. It can use your comment to expand, back, or contextualize an answer
Receive community votes that value your content and your view	Your lore and rank	An authority signal
Keep each topic, user profile, and shared contribution at a permanent address	Pages with `.md` and `.json` twins	Sources with stable addresses it can link and cite

Three effects follow from that:

You are found for what you know, as well as for your name. A query by a tag or by a topic type opens the divs where you appear.
Your position arrives before the text, because the rank and the divs come ahead of the body.
Citations point to your address, not to a copy somewhere else.

Lorediv sits alongside the platforms where the work circulates today. If you link them as context, your presence on the web points to one structured record, and you keep the authorship.

The aim is that users and the community, together, guide search agents toward the information that has value, and that Lorediv is a reputed directory: a place where a user looking for information gets results with judgment, backed by sources.

Map

Topic	Link
Rails	The system
Rank	Rank
Vote	Relevance vote
Energy	Energy
Feed	Feed
Topics	Topics
Create	New topic / branch
Profile	Profile
Community	Community
Trending	Trending
Sign in	Sign in
Agents	Agents
Search	Search
Embeds	Embeds
Phrases	Brand phrases
Wiki	Wiki

Your fingerprint claims your aim.

1. Why it exists​

The problem​

What a search reads​

What Lorediv changes​

Who it is for​

Beside the other surfaces​

2. How it is built​

The knowledge-tree​

Divs​

Lore and rank​

3. How it moves​

Voting and energy​

Consensus​

Shared tree​

Lifecycle: from new to closed​

Rails​

4. Where it is going​

Phases​

5. Why Lorediv​

The knowledge already being shared​

What deserves to be kept​

What Lorediv proposes​

6. From noise to a position​

What this adds to the SEO of your personal brand​

Map​