Incentive Lab

AI contributor reward calculator

Does useful work pay for itself?

Model capped rewards for accepted work and see whether customer revenue covers operating costs before token support.

Use my own records

Local processing · No account · No wallet connection

What would you like to check?

Choose a fictional scenario to run it immediately, then change the assumptions.

Explore the calculations and common mistakes

Make it your own

Edit the form or import the example-shaped JSON. Input reference

Edit the inputs

Inputs stay in this tab and clear on reload. No automatic upload or wallet access. Maximum 128 KiB.

Report text for manual copy

From your records to a reviewable result

  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.
Read the method and example

Where this tool fits

An explicit simulation of budget conservation, contributor caps and organic contribution, rather than an APY or token-price story.

Scope: No live subnet data, fraud detection, Bittensor emission replication, staking recommendation or token distribution.

有用工作激励实验：可直接使用表单，也可导入 JSON。先运行虚构示例理解结果，再切换到自己的材料。输入仅在当前页面处理。查看中文说明。

Compare with established tools

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.

Official product descriptions reviewed 19 September 2026. These are alternatives, not partners or endorsements.

  • Bittensor

    Subnets define incentive mechanisms; miners produce commodities and validators evaluate them.

  • Gensyn

    Research and products around verifiable AI, reproducible execution and feedback-linked learning.

What does Incentive Lab do?

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.

By the AGI Scorecard team. Method and sources reviewed . Read the method.

Questions before you start

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.

Continue your review

Agent EvidenceReview task-specific agent evaluations with sample deduplication, version boundaries and uncertainty intervals.Stable ReconcileReview invoices against your recorded stablecoin transfers. Keep partial payments, wrong assets and pending transactions visible.

Use this workflow in your AI assistant

Connect the MCP server to read sources and run these calculations from a supported client. Remote calls send parameters to the server; the browser worksheet remains local.

Get the MCP connection and citation guide