Start Task logo

Start Task

Organization
devoxx
start-task

Create a feature branch for a backlog task, switch to it, and start implementation. Use when the user says "start task-123", "work on task-123", "implement task-123", or invokes /start-task with a task ID.

Overview

Publisherdevoxx
RepositoryDevoxxGenieIDEAPlugin
Skill namestart-task
Stars
684
Forks
103
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by devoxx on GitHub. Read the source before you install it.

Installation

Install the Start Task AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/devoxx/DevoxxGenieIDEAPlugin/tree/master/.claude/skills/start-task
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/devoxx/DevoxxGenieIDEAPlugin.git /tmp/DevoxxGenieIDEAPlugin
mkdir -p .claude/skills
cp -r /tmp/DevoxxGenieIDEAPlugin/.claude/skills/start-task .claude/skills/start-task
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Start Task in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Start Task on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Start Task is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Start Task

Context

  • Current branch: !git branch --show-current
  • Working tree status: !git status --short
  • Existing branches: !git branch --list 'feature/task-*'

Your task

Create a feature branch for a backlog task and begin implementation.

The user will provide a task ID (e.g. task-123 or 123). If no task ID is provided, check the argument $ARGUMENTS for the task reference.

Step 1 — Load the task

  • Normalize the input: if the user gave just a number like 123, treat it as task-123.
  • Use mcp__backlog__task_view to read the full task details: title, description, acceptance criteria, and any referenced files.
  • If the task is not found, use mcp__backlog__task_search to locate it.
  • Print a brief summary of the task for the user.

Step 2 — Ensure a clean working tree

  • Check git status. If there are uncommitted changes, warn the user and ask whether to stash them before proceeding.
  • Ensure we are on the main branch. If not, ask the user if they want to switch.

Step 3 — Create and switch to a feature branch

  • Pull latest changes on main: git pull --rebase.
  • Derive a branch name from the task: feature/task-{id}-{slugified-title} (lowercase, hyphens, max ~60 chars).
    • Example: task 113 "Split app.css into native CSS modules" → feature/task-113-split-css-modules
  • Create and switch to the branch: git checkout -b <branch-name>.

Step 4 — Mark the task as in-progress

  • Use mcp__backlog__task_edit to set the task status to In Progress.

Step 5 — Plan and implement

  • Analyze the task description and acceptance criteria carefully.
  • Read all files referenced in the task, plus any related code you need to understand.
  • Create a plan and present it to the user for approval before writing code.
  • Once approved, implement the changes following the project's patterns and conventions.
  • After implementation, run the full verification suite:
    bash
    npm run lint && npm run typecheck && npm test && npm run build:app && npx playwright test
  • Fix any issues found by the verification suite.

Step 6 — Report

  • Summarize what was implemented and which acceptance criteria were addressed.
  • Remind the user they can use /close-task-commit-push-pr when ready to ship.

Rules

  • Always create the branch from an up-to-date main branch.
  • Never start implementation without showing the plan to the user first.
  • Follow existing code patterns and conventions in the project.
  • Do not use interactive git flags (-i).
  • If the working tree is dirty, never silently discard changes.

Frequently asked questions

What does the Start Task AI skill do?

Create a feature branch for a backlog task, switch to it, and start implementation. Use when the user says "start task-123", "work on task-123", "implement task-123", or invokes /start-task with a task ID.

Why use Start Task on TypingMind?

Because you install it once and use it with any model. Start Task is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Start Task in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/devoxx/DevoxxGenieIDEAPlugin/tree/master/.claude/skills/start-task. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Start Task?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Start Task?

As many as you like. As long as a model supports skills, you can use Start Task with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Start Task AI skill free?

Yes. It is published on GitHub by devoxx under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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