# Prolog Reasoner

> Use this tool when you need to perform logical deductions, solve complex rules-based problems, or validate knowledge graphs. The Prolog Reasoner takes logical queries and rules as input and outputs inferred conclusions, providing a powerful logic calculator for large language models. It is ideal for use cases involving expert systems, decision support, and knowledge representation.

Canonical page: https://skillsregistry.net/skills/io-github-rikarazome-prolog-reasoner  
JSON: https://api.skillsregistry.net/v1/skills/io-github-rikarazome-prolog-reasoner

## Description

SWI-Prolog as a logic calculator for LLMs

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.2.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.rikarazome%2Fprolog-reasoner)
- **Repository:** <https://github.com/rikarazome/prolog-reasoner>

## 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": "io-github-rikarazome-prolog-reasoner"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-rikarazome-prolog-reasoner` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-rikarazome-prolog-reasoner/pull`

---
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