# PictMCP

> Use this tool when you need to generate pairwise test cases for AI assistants, solving the problem of efficient test coverage and reducing the complexity of testing multiple input combinations. PictMCP takes input parameters and produces optimized test suites as output, utilizing the PICT algorithm and running locally via WebAssembly. Ideal for use cases where comprehensive testing is required, such as AI model validation and software development.

Canonical page: https://skillsregistry.net/skills/takeyaqa-pictmcp  
JSON: https://api.skillsregistry.net/v1/skills/takeyaqa-pictmcp

## Description

Provides pairwise test generation for AI assistants using the PICT algorithm, running locally via WebAssembly.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ehz34jf3ex)
- **Repository:** <https://github.com/takeyaqa/PictMCP>

## 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": "takeyaqa-pictmcp"
    }
  }
}
```

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