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YesNoError

YesNoError (YNE) — a reference card for a crypto project: what the product does and how verifiable the project’s key claims are; also — alignment with the Decentralized AI thesis (DecAI Fit).

YesNoError — an AI/Agents / DeSci project: an “AI Agent for Breakthrough Research Notifications” and a platform that (per the whitepaper) uses LLM agents for mass auditing of scientific papers (finding errors/methodological problems) and issues the YNE token on the Solana network.

Disclaimer

Important: this page is a reference overview of the project. Within DecAIHub, we separately record a verification based on open sources within the AI thesis (what is real AI/onchain/why a token, and which sources this is based on).
This is not financial advice and not a recommendation to buy/sell/hold any asset. We do not assess price, returns, or entry/exit timing.
Conclusions are based on publicly available materials found as of the verification date. The absence of confirmation does not imply the absence of the technology.

TL;DR (for readers who are not into AI)

  • What it is: a service/platform for searching and checking scientific publications, where LLM agents help find errors.
  • Who it’s for: researchers, editors, journalists and users who need to quickly verify scientific claims.
  • Why onchain/token: the YNE token is used to pay for audits and for the collective selection of priority topics (voting/campaigns) per the whitepaper.
  • What you can actually touch (Tier‑1): the product’s web interface at yesnoerror.com.

How it works (very briefly)

  1. The user does: searches for/adds a publication or uploads a document for checking.
  2. The system does: extracts the text, splits it into chunks, uses RAG and a set of specialized “reviewer agents” (math/methodology/logic/reference) for the analysis.
  3. The user gets: a structured report with the problems found and recommendations/next steps.
  4. Where the blockchain is: the YNE token is onchain (Solana), used as an economic tool for managing priorities and payments.
  5. Token role (if any): on-demand audits + community campaigns/voting; the whitepaper describes buyback&burn mechanics.

Quick links: AI thesis fit

Project passport

Field Value
Project name YesNoError
Also known as (aliases) YNE; $YNE; YesNoError (YNE)
Logo (logo) ../assets/237_yesnoerror_logo.png
Token symbol (ticker) YNE
Category AI/Agents | DeSci
Primary chain (chain) Solana
Type non-EVM
Network status mainnet
Consensus (consensus) PoS (Solana)
Launch date (launch_date) —
Project status (status) active
Token (standard) SPL
Token contract 7D1iYWfhw2cr9yBZBFE6nZaaSUvXHqG5FizFFEZwpump
Token model (token_type) utility (governance + campaigns + buyback + burn)
Max supply —
Issuance —
Tokenomics (tokenomics, brief) on-demand audits + community voting/campaigns; buyback&burn (whitepaper)
Governance voting/campaigns via the token (whitepaper)
Admins/keys —
Audit —
Bug bounty —
Team (team) —
Funding (investors/funding) —
AI component (ai_component) LLM agents for scientific paper review
Use‑case (use_case) research error/quality checking
DecAI Fit — AI thesis fit 3/6 — medium alignment with the Decentralized AI thesis
DecAI Fit component summary 3 / 1 / 2 / 2
Last verified 2026-02-11

General project overview

YesNoError is an initiative that proposes using LLM agents for a large‑scale “literature audit”: scanning and checking scientific papers for errors (mathematical/methodological/logical/reference errors), and in the future also assigning quality ratings and looking for signs of fraud. The whitepaper describes the architecture ingestion → parsing → chunking/embeddings (RAG) → multi‑agent orchestration → structured report.

Features/modules

  • Document pipeline: upload/text extraction/splitting into chunks and RAG.
  • A set of specialized “reviewer agents”: Math Checker, Methodology Checker, Factual/Reference Checker, Logic Checker.
  • Reports: a structured report on errors/risks and next steps.
  • Token mechanics: on-demand audits and community campaigns/voting (whitepaper).

Typical scenarios

  • Scenario 1: a researcher uploads a manuscript/paper → receives a report with the problems found.
  • Scenario 2: the community proposes a “thematic audit” (e.g., a research area) → token holders vote and pool resources for the campaign.

Getting started (wallet/network)

  • What you need: access to the website/product; a Solana wallet — if interacting with the YNE token.
  • Network/chain: Solana.
  • Fees: Solana fees for transfers/DEX operations with YNE.

Architecture/tech (non‑AI)

  • Components: web interface/platform; offchain document processing pipeline; onchain YNE token (Solana).
  • Participant roles: users (audit requests), participants/holders (voting/campaigns), platform operators.
  • Where logic runs: document analysis — offchain; the token — onchain.
  • Dependencies: publication sources (arXiv/PubMed/user uploads — per the whitepaper); Solana infrastructure for the token.

Token/economics (expanded, no forecasts)

  • Token utility: the whitepaper describes payment for AI audits and a community‑driven prioritization mechanism (voting/campaigns) with resource pooling.
  • Protocol necessity drivers: the token is used as a means of funding computations and selecting priorities.
  • Who pays fees: users/participants for onchain operations.
  • Where fees go: network fees — to Solana validators; within the project’s model, buyback&burn from revenue is mentioned (whitepaper).
  • Issuance/burn: the whitepaper describes buyback&burn; supply/Max supply is listed on CMC.
  • Security/incentive mechanisms: campaigns/voting; burn mechanics as an element of sustainability (whitepaper).
  • Distribution and token issuance schedule: — (not disclosed in the Tier‑1 shown).
  • Treasury: —.

Governance

  • Who makes decisions: per the whitepaper, token holders participate in prioritizing audit topics via voting/campaigns.
  • How protocol parameters change: —.
  • Where decisions are discussed/made: community channels (X/Telegram) and campaign processes (whitepaper).
  • Keys/multisig: —.

Security and incidents

  • Audits: not found in Tier‑1 sources.
  • Bug bounty: —.
  • Incidents: not found in Tier‑1 sources.
  • Threat model: risks of LLM errors/hallucinations and risks of misinterpreting reports without human review.

Project status and timeline

  • Current status: the website and whitepaper are public; the YNE token is on Solana.
  • Key releases/milestones: whitepaper v1.0 (on the website).
  • Roadmap: the roadmap section is in the whitepaper.

Ecosystem/integrations

  • Integrations: Solana wallets/DEX infrastructure for the token; publication sources (arXiv/PubMed, etc. — per the whitepaper).
  • Partners: —.
  • Where it’s actually used: the web interface as “research discovery” (website).

AI component of the project

  • What is real AI here? the whitepaper describes a RAG + multi‑agent “AI reviewers” pipeline for analyzing scientific papers and generating reports.
  • What is truly onchain? the YNE token (SPL, Solana) and the onchain operations associated with it.
  • Why is a token needed? payment for audits/campaigns and a community prioritization mechanism (voting), plus buyback&burn (whitepaper).
  • Red flags (based on the information found): onchain‑washing — high (apart from the token, no onchain logic is described); AI‑washing — moderately low (there is a technical description); what to double‑check — the quality/accuracy of the reports and the existence of a public demo with examples.

DecAI Fit component summary

  • DecAI Fit: 3/6 — medium alignment with the Decentralized AI thesis
Component Level Score
AI reality high 3
Onchain necessity low 1
Token necessity medium 2
Evidence Tier‑1 present 2
Details

AI reality

AI_0 — AI intent (Tier‑1 roadmap) (1/0)

  • AI_0 (decision): 0
  • Claim (one line): the AI component is described as a working pipeline (AI_1/AI_4), so this is not “intent only”.
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): AI_0 applies only if AI_1..AI_4 = 0.
  • Conflict note (if any): —

AI_1 — what the AI does (1/0)

  • AI_1 (decision): 1
  • Claim (one line): LLM agents analyze papers and produce a report on errors/risks (math/methodology/logic/reference).
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): the roles of the agents and the analysis tasks are described.
  • Conflict note (if any): —

AI_2 — demos/examples (1/0)

  • AI_2 (decision): 1
  • Claim (one line): the website provides access to the product/interface (research discovery/adding materials).
  • Evidence: Tier‑1 — https://yesnoerror.com/
  • Why sufficient / why not (one line): there is a public interface of the service as a demonstration of how it works.
  • Conflict note (if any): the quality/examples of the reports were not verified in the text.

AI_3 — metrics/quality (1/0)

  • AI_3 (decision): 0
  • Metrics: —
  • Context (version/date/how measured): —
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): quantitative accuracy/quality metrics are not provided.
  • Conflict note (if any): —

AI_4 — tech description/architecture/versions (1/0)

  • AI_4 (decision): 1
  • Claim (one line): the whitepaper describes ingestion/parsing, RAG (embeddings/vector db) and multi‑agent orchestration.
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): there is a technical description of the pipeline and the agent roles.
  • Conflict note (if any): model versions/repositories are not specified.

Onchain necessity

OC_1 — contracts/addresses/chain (1/0)

  • OC_1 (decision): 1
  • Chain: Solana
  • Addresses/identifiers: SPL mint: 7D1iYWfhw2cr9yBZBFE6nZaaSUvXHqG5FizFFEZwpump
  • Evidence: Tier‑1 — https://explorer.solana.com/address/7D1iYWfhw2cr9yBZBFE6nZaaSUvXHqG5FizFFEZwpump?cluster=mainnet
  • Why sufficient / why not (one line): the token’s mint address is confirmed via Solana Explorer.
  • Conflict note (if any): —

OC_2 — onchain beyond just a token (1/0)

  • OC_2 (decision): 0
  • What useful logic is onchain: apart from the token, smart contracts/onchain rules are not described in Tier‑1.
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): the product and the AI pipeline are described as offchain.
  • Conflict note (if any): —

OC_3 — onchain is critical (1/0)

  • OC_3 (decision): 0
  • “Replace the blockchain” test: the core function (paper analysis) can exist without a blockchain; onchain criticality is not proven.
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): there is no Tier‑1 argument that the product breaks down without a blockchain.
  • Conflict note (if any): —

Token necessity

TK_0 — no token (1/0)

  • TK_0 (decision): 0
  • Claim (one line): the project has a token, YNE (SPL, Solana).
  • Evidence: Tier‑1 — https://explorer.solana.com/address/7D1iYWfhw2cr9yBZBFE6nZaaSUvXHqG5FizFFEZwpump?cluster=mainnet
  • Why sufficient / why not (one line): the token contract is public.
  • Conflict note (if any): —

TK_1..TK_4 (1/0)

TK_1 — payment for the service (1/0)

  • TK_1 (decision): 1
  • Claim (one line): the token is used for on-demand research reviews/audits (whitepaper).
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): the tokenomics describes the token’s role in paying for services.
  • Conflict note (if any): —

TK_2 — incentives/collateral/penalties (1/0)

  • TK_2 (decision): 0
  • Claim (one line): collateral/penalties/staking as a mandatory protocol mechanic are not described in Tier‑1.
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): there are campaign and buyback&burn mechanics, but no “bond/slash”.
  • Conflict note (if any): —

TK_3 — governance (1/0)

  • TK_3 (decision): 1
  • Claim (one line): the token is used for voting/campaigns (community-driven prioritization of research audits).
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): a voting mechanism for selecting priorities is described.
  • Conflict note (if any): —

TK_4 — token is replaceable (1/0)

  • TK_4 (decision): 0
  • Claim (one line): the replaceability of the token (with a subscription/USDC) is not substantiated in Tier‑1.
  • Evidence: Tier‑1 — https://yesnoerror.com/whitepaper
  • Why sufficient / why not (one line): the tokenomics is tied to community campaigns and the burn mechanics.
  • Conflict note (if any): —

Evidence (table)

Tier Source What it proves
Tier‑1 https://yesnoerror.com/whitepaper AI architecture (RAG + multi‑agent), token utility (audits/voting/buyback&burn)
Tier‑1 https://yesnoerror.com/ access to the product/interface (demo/example)
Tier‑1 https://explorer.solana.com/address/7D1iYWfhw2cr9yBZBFE6nZaaSUvXHqG5FizFFEZwpump?cluster=mainnet onchain SSOT: mint of the YNE SPL token (Solana Explorer).
Tier‑2 https://solscan.io/token/7D1iYWfhw2cr9yBZBFE6nZaaSUvXHqG5FizFFEZwpump Explorer/aggregator of onchain data (for navigation).
Tier‑2 https://coinmarketcap.com/currencies/yesnoerror/ Aggregator: reference profile and links (not Tier‑1).
Tier‑2 https://www.coingecko.com/en/coins/yne Aggregator: reference profile and links (not Tier‑1).

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