# InferFund

> InferFund — theabbie-inferfund. Use this tool when you need to accelerate progress on open mathematical problems by donating AI inference capabilities. InferFund solves the problem of limited computational resources for advancing mathematical research by crowdsourcing AI inference. It takes in open mathematical problems and AI models as input and outputs accelerated research progress through collaborative computation.

Canonical page: https://skillsregistry.net/skills/theabbie-inferfund  
JSON: https://api.skillsregistry.net/v1/skills/theabbie-inferfund

## Description

Donate AI inference to advance open mathematical problems.

## Trust

- **Trust score (0–1):** 0.93
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/theabbie/InferFund)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "theabbie-inferfund"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/theabbie-inferfund` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/theabbie-inferfund/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt