# tasker

> Use this tool when you need to manage complex tasks and stories in a hierarchical structure, and want to streamline task creation, editing, and status updates. It solves problems of task organization and tracking, allowing AI agents to efficiently handle multiple tasks and stories stored as Markdown files. Through the Model Context Protocol, it provides a simple interface for inputting task updates and outputting updated task status.

Canonical page: https://skillsregistry.net/skills/greendwin-mcp-tasker  
JSON: https://api.skillsregistry.net/v1/skills/greendwin-mcp-tasker

## Description

Enables AI agents to manage hierarchical tasks and stories stored as Markdown files, providing tools for creating, listing, editing, and updating task status through the Model Context Protocol.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/gs4flk9306)
- **Repository:** <https://github.com/greendwin/mcp-tasker>

## 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": "greendwin-mcp-tasker"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/greendwin-mcp-tasker` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/greendwin-mcp-tasker/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