Cowrie Research

kaito-yaps

3 min read

Kaito Yaps

  • Name: Kaito Yaps
  • URL: https://docs.kaito.ai/kaito-yaps-tokenized-attention.md
  • Category: tokenized-attention protocol / creator-attribution infrastructure / reputation-and-reward routing middleware
  • Summary: Kaito Yaps turns attention scoring into routing infrastructure. The score is only half the story; the real leverage is in topic framing, identity mapping, leaderboard publication, and the launchpad surfaces that route rewards and visibility.
  • What it does:
    • Computes Yaps scores as AI-derived proof-of-attention using Proof-of-Work, Proof-of-Exchange, and Proof-of-Insight signals
    • Publishes public Yapper Leaderboards that rank creators by contribution and influence for a specific brand or topic
    • Exposes Yaps scores through a public API so third-party builders can use tokenized-attention data in their own applications and reward programs
    • Publishes Yaps data onchain through EAS on Base, making the score composable for onchain integrations even though the identity reference remains the X username rather than a wallet-native account
    • Embeds Yaps inside the broader Kaito Connect network, where launchpad voting is meant to decide which brands or topics get future attention-allocation surfaces
    • Positions the combined system as a fairer alternative to agency-led creator selection, subjective influence scoring, and platform-controlled attention routing
  • Key claims:
    • The Kaito docs explicitly frame Yaps as a response to weak attention proxies such as likes, views, impressions, and follower counts, arguing that richer AI-derived signals are needed to measure real influence. That makes Yaps analytically closer to reputation middleware than to ordinary campaign analytics.
    • The three-part scoring split — Proof-of-Work, Proof-of-Exchange, and Proof-of-Insight — matters because it decomposes attention into production volume, engagement quality, and perceived originality rather than presenting one monolithic opaque rank.
    • Yaps Open Protocol is the clearest signal that this should live in the corpus. Kaito exposes the score through a public API and says the data is available onchain via EAS on Base, which turns attention scoring into a reusable primitive for downstream builders instead of keeping it trapped inside a single app.
    • The leaderboard layer is a separate control surface from the score itself. Topic-specific and brand-specific ranking determines who becomes publicly legible as influential, which creators brands can identify, and which content users discover first.
    • The launchpad layer is another distinct mechanism. Kaito says market forces, not a centralized operator, should determine how attention is distributed across brands, which means Yaps is part of a broader market design for allocating visibility rather than only a measurement tool.
    • Important chokepoints still remain: Kaito controls the scoring models, topic framing, data access defaults, and the mapping from offchain social identities to onchain-attested score records. The docs also note that onchain Yaps are tied to usernames and scores only, with no direct wallet linkage, so downstream integrations inherit Kaito’s identity model rather than a purely wallet-native one.
    • Kaito Yaps is a strong comparison class for Talent Protocol, OpenRank, SourceCred, Nomis, and Orange Protocol because it shows how contributor legibility can migrate from activity tracking into attention-weighted discovery, reward allocation, and market-facing brand coordination.

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