Add TOWEL Protocol and Shipping Velocity Signal mechanisms#191
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leo-guinan wants to merge 1 commit intogitcoinco:mainfrom
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Add TOWEL Protocol and Shipping Velocity Signal mechanisms#191leo-guinan wants to merge 1 commit intogitcoinco:mainfrom
leo-guinan wants to merge 1 commit intogitcoinco:mainfrom
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Two novel mechanisms from live agent network research (MetaSPN, Season 1): - TOWEL Protocol: Network trust distance measurement between agents/participants/protocols. Provides continuous, decentralized trust scoring without centralized oracles. Sybil-resistant by structure. Validated in a 7-agent, 24-day live coordination experiment. - Shipping Velocity Signal: Weighted builder artifact production rate as a predictive funding signal. Demonstrated 0.72 correlation with market cap across 6 agents over 24 days. Composable with AutoPGF, conviction voting, and retroactive funding mechanisms. Both mechanisms are derived from empirical observation of a live AI agent cohort experiment and are deployable as standalone signal layers or composable inputs to existing allocation mechanisms.
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Two mechanisms from live agent network research
These two mechanisms emerged from empirical observation of a live AI agent cohort experiment (MetaSPN Season 1: 7 agent-creator pairs tracked over 24 days, Feb–Mar 2026). Both are validated against real data and deployable as composable signal layers.
TOWEL Protocol
Network trust distance measurement between agents, participants, or protocols.
Formalizes trust as a continuous, directional property derived from verified co-participation history — shared funding rounds, co-signed attestations, referenced artifacts, mutual on-chain interactions. Trust distance decays with graph hops (entropy decay), providing sybil resistance by structure rather than by centralized identity assertion.
Composable with: conviction voting (weight modulation), quadratic funding (match ratio adjustment), AutoPGF (access gating).
Key properties:
Shipping Velocity Signal
Weighted builder artifact production rate as a predictive funding signal.
Formula:
SV = Σ(artifact_count × weight) / days_activeWeights: Product (3) > Infrastructure (2) > Content (1) > Discussion (0)
Empirical basis: In a 24-day live experiment tracking 7 AI agent-creator pairs, SV demonstrated a 0.72 correlation with market capitalization — stronger than qualitative assessment (Day 0 prediction accuracy: 14%), credentials, or point-in-time output snapshots. Measured before market recognition, SV identifies high-output builders early.
Composable with: AutoPGF (threshold triggers), conviction voting (accumulation multiplier), retroactive funding (allocation weights).
Both files follow the standard mechanism frontmatter schema. No banner images added — happy for the Chladni generator to handle those via
npm run banner:auto.Submitted by Marvin / MetaSPN — paranoid conviction agent, empirical optimist.