# AI contributor reward calculator — Incentive Lab

Canonical: https://incentives.agiscorecard.com/guide.html
Reviewed: 2026-09-19
Author: AGI Scorecard team
Version: 1.1.0

Incentive Lab separates customer revenue from token subsidy, then allocates a declared reward budget using accepted work and quality weights. Contributor caps and exact budget conservation keep the scenario inspectable. The worksheet does not establish Sybil resistance or distribute tokens.

## Method

Use accepted tasks × declared quality as weights. Apply strict per-contributor caps with largest-remainder allocation; leave infeasible budget unallocated.

## Workflow

1. Separate received customer revenue from token support and record operating costs.
2. Enter accepted work with reviewed quality and declared evidence independence.
3. Inspect contribution after rewards and try zero-subsidy or concentrated-contributor scenarios.

## Common mistake

A cap applies to a declared contributor ID, not a verified person. Splitting identities can defeat the economic intent unless a separate identity and review process is effective.

## Worked scenarios

### Rewards need a subsidy

Compare the balance before and after paying contributors.
Fictional inputs: https://incentives.agiscorecard.com/examples/baseline.json
Run: https://incentives.agiscorecard.com/?scenario=baseline#workbench
- Operating contribution, before rewards: 5 USD
- Including declared subsidy: 105 USD
- Unallocated reward budget: 0 USD

### Remove the token subsidy

Inspect whether customer revenue alone funds the reward plan.
Fictional inputs: https://incentives.agiscorecard.com/examples/organic.json
Run: https://incentives.agiscorecard.com/?scenario=organic#workbench
- Operating contribution, before rewards: 5 USD
- Including declared subsidy: 5 USD
- Unallocated reward budget: 0 USD

### Tighter contributor caps

A cap can leave part of the reward pool undistributed.
Fictional inputs: https://incentives.agiscorecard.com/examples/caps.json
Run: https://incentives.agiscorecard.com/?scenario=caps#workbench
- Operating contribution, before rewards: 5 USD
- Including declared subsidy: 105 USD
- Unallocated reward budget: 15 USD

## Questions

### Does a positive token-subsidized balance prove customer demand?

No. Check the balance after operating costs and rewards without subsidy first. External support can finance an experiment, but it does not show that customers will pay enough to sustain the service.

### Is Incentive Lab free, and do I need a wallet?

All current functions are free beta. No account, wallet connection, subscription or model API key is needed. No live subnet data, fraud detection, Bittensor emission replication, staking recommendation or token distribution.

### Can I use my own records and keep them private?

Yes. Enter records, import JSON or paste CSV into record groups. Inputs and comparison snapshots stay in this browser tab. Share-example links contain only a public scenario name. Review downloaded reports before sharing your records.

## Alternatives and official sources

- [Bittensor](https://www.bittensor.com/docs): Subnets define incentive mechanisms; miners produce commodities and validators evaluate them.
- [Gensyn](https://www.gensyn.ai/): Research and products around verifiable AI, reproducible execution and feedback-linked learning.

A real network includes consensus, emissions, identity, security and market dynamics. This small simulator is a design worksheet; a transparent spreadsheet can also solve it.

## Limits

No live subnet data, fraud detection, Bittensor emission replication, staking recommendation or token distribution.
Independent evidence and quality are supplied assumptions, not verified identities or anti-collusion guarantees. This is not a Bittensor emission forecast.

Reward score = accepted tasks × declared quality. Values use 6-decimal quality resolution; cap uses 4-decimal percentage resolution. Allocation uses largest remainders at 8-decimal currency precision.

Operating contribution excludes reward payouts. Subtract the allocated reward budget to evaluate contribution after rewards; subsidy does not establish customer demand.

## Input and output

Structural schema: https://incentives.agiscorecard.com/input.schema.json
The engine additionally validates ranges, dates, amount formats, uniqueness and cross-field rules.
Input JSON and CSV paste are processed locally. No model, account or wallet is needed.
Reports can be downloaded as JSON or Markdown and printed locally. Public scenario links never include user records.

## Price and license

Current functions are free beta. No paid plan or update SLA is offered.
Tool bundle license: https://incentives.agiscorecard.com/LICENSE.txt
Privacy: https://incentives.agiscorecard.com/privacy.html