# Quint

> Use this tool when you need to verify distributed system designs through mathematical modeling, solving problems such as type-checking, simulation, and model checking. It provides six tools that support various inputs, including specifications and test definitions, and outputs counterexample traces and verification results. Ideal for use cases requiring formal verification workflows, such as ensuring correctness and reliability of complex system designs.

Canonical page: https://skillsregistry.net/skills/dpdanpittman-quint  
JSON: https://api.skillsregistry.net/v1/skills/dpdanpittman-quint

## Description

Provides six tools wrapping the Quint CLI for formal verification workflows. Supports type-checking specifications, running random simulations with invariant checking and counterexample traces, executing named test definitions, performing exhaustive model checking via the Apalache backend, parsing specifications into IR JSON, and looking up Quint language documentation. Designed for verifying distributed system designs through mathematical modeling.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/dpdanpittman-quint)
- **Repository:** <https://github.com/dpdanpittman/mcp-server-quint>

## 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": "dpdanpittman-quint"
    }
  }
}
```

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