# CK-ASK

> Use this tool when you need to interrupt and guide AI-driven development workflows with human input, solving problems of automated processes lacking user oversight. CK-ASK enables AI assistants to pause and collect feedback through terminal or dialog modes, providing a flexible interface for user instructions. It is ideal for use cases requiring collaborative coding and feedback integration, such as pair programming with AI assistants.

Canonical page: https://skillsregistry.net/skills/gagmeng-ck-ask  
JSON: https://api.skillsregistry.net/v1/skills/gagmeng-ck-ask

## Description

CK-ASK is an AI conversation pause tool that enables interruption and user input during AI-driven development workflows. It allows AI assistants to wait for human instructions by pausing responses and collecting feedback before continuation. The tool operates in two modes: terminal mode for direct command-line input prompts, and dialog mode providing a visual popup interface through a VS Code extension. It integrates with various AI coding assistants including Windsurf and Cursor editors.

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/gagmeng-ck-ask)
- **Repository:** <https://github.com/gagmeng/ck-ask>

## 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": "gagmeng-ck-ask"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/gagmeng-ck-ask` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/gagmeng-ck-ask/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