Earn Layer
What Earn Is
The Earn Layer is the protocol’s growth mechanism — how users build REP through active contribution to the Repute intelligence ecosystem.
Earn is not passive. It requires producing verifiable structural intelligence, onboarding genuine creators, or maintaining accurate predictions over time.
How to Earn REP
Submit Structural Insights
Contribute signal analysis to the protocol. This includes:
- Identifying structural anomalies in monitored channels (backed by observable data)
- Flagging emerging narratives with supporting creator density evidence
- Documenting creator graph connections (which creators are cross-referencing which narratives)
Submissions are validated by subsequent model output. If the structural insight is confirmed by the models over the following observation window, REP_Contribution is awarded.
Earning rate: Scales with insight precision, not volume.
Accuracy Scoring
The highest-value REP earn path. When you identify:
- A channel with high structural readiness (high AVI + SIS + NSM + high BPM) and it subsequently demonstrates a verifiable breakout
- A channel with high fragility signals (high TRI, low SIS) and it subsequently collapses
…REP_Accuracy is awarded.
Accuracy scoring requires making predictions through the protocol interface, not just observing. Retrospective claims do not qualify.
Creator and Channel Onboarding
Refer Telegram channel creators to the protocol. When a referred creator:
- Joins and verifies their channel
- Achieves SIS > 50 within 60 days
- Maintains structural quality for 90 days
REP_Network is awarded to the referring account.
Anti-gaming: Referring accounts that fail structural thresholds (bot-driven channels, hollow communities) earns nothing. Referring accounts that are discovered to be fake or manipulated triggers an integrity penalty on the referring user.
Critical: Earn Does Not Influence Core Models
Earn REP — REP earned through protocol contributions — affects only your reputation weight within the Repute protocol. It does not influence, modify, or feed back into the underlying intelligence model outputs (AVI, SIS, NSM, BPM, TRI) for any channel.
Model scores are computed exclusively from observable public Telegram data. No amount of REP earning can change a channel’s structural score. The models are isolated from the earn layer by design.
Earn vs. Channel Score
| What Earn Affects | What Earn Does NOT Affect |
|---|---|
| Your REP score (0–1000) | AVI scores of any channel |
| Your protocol tier | SIS scores of any channel |
| Your governance influence weight | NSM, BPM, TRI of any channel |
| Your access to advanced features | The Mindshare Arena rankings |
REP_Integrity and Earn Risks
Certain earn-adjacent behaviors reduce REP_Integrity:
- Submitting low-quality signals at high volume (spam)
- Attempting to manipulate model outputs through coordinated fake submissions
- Referral farming (referring channels that are found to be bot-driven)
- Account coordination to game accuracy scoring
REP_Integrity penalties are persistent and partially irreversible. The protocol monitors for coordination patterns across accounts.