> For the complete documentation index, see [llms.txt](https://docs.rubyscore.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rubyscore.io/overview/problems-rubyscore-solves.md).

# Problems RubyScore Solves

**Bots distort metrics.** Up to 70–80% of airdrop and campaign participants can be fake accounts. RubyScore filters them out, keeping only real users.

**Unfair campaigns.** Rewards are often distributed equally even when contributions differ. RubyScore accounts for real activity and fairly rewards genuine contributors—within a single blockchain and across multiple chains.

**High acquisition costs.** Teams spend budgets on click-through tasks that don’t create real engagement. With RubyScore, projects can target users who actually interact with the ecosystem.

**Fragmented identity.** A single user’s activity is scattered across different blockchains. RubyScore unifies it into a single, reputation layer.

**In short, RubyScore builds the trust foundation for Web3:**

* users build on-chain reputation and unlock new opportunities,
* projects protect budgets, find real participants, and distribute rewards fairly,
* ecosystems grow through authentic on-chain activity.