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Task

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mweinbach
task

Hand ordinary chat off to durable Task mode when the user explicitly invokes /task or requests a managed task. Complexity, progress tracking, or a need for a plan alone does not authorize a handoff; continue that work in the current chat.

Overview

Publishermweinbach
Repositoryagent-coworker
Skill nametask
Stars
156
Forks
14
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the 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.
  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/mweinbach/agent-coworker.git /tmp/agent-coworker
mkdir -p .claude/skills
cp -r /tmp/agent-coworker/skills/task .claude/skills/task
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 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 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 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.

Task Mode

Task mode is a one-way handoff from the current chat to a managed task. A successful createTask call replaces the chat with the task workspace and locks the source chat until the task reaches completed, failed, or cancelled.

Decide whether to create a task

Create a task only when the user explicitly invokes this skill, /task, or directly requests managed Task mode. A request to complete substantial work is not by itself a request to change modes.

Continue other work in standard chat, using a plan or checklist when useful. Do not promote merely because work is complex, has several steps, or may span sessions.

Gather enough detail

Treat actionable requests as instructions to proceed within their authorized scope. User instructions override this skill's defaults, subject to higher-priority instructions and enforced tool boundaries. If an applicable skill requirement still prevents progress, quote it and identify this SKILL.md; do not silently stop or ask the user to repeat an authorization already given.

Before calling createTask, make sure the conversation establishes:

  • A concise title and concrete objective.
  • Relevant background, current state, and constraints for the handoff.
  • Fixed requirements and at least one observable acceptance criterion.
  • A complete initial work plan with stable local keys, dependencies, and expected outputs.
  • Material decisions already made, including any reasonable reversible assumptions.
  • Any user-requested review or explicit approval gate. A final reviewable delivery does not by itself require a blocking approval step; do not invent a gate when none was requested or otherwise required.

Infer implementation details and reversible defaults yourself. Ask the user only when missing information would materially change scope, risk, or the delivered result. Bundle missing questions into one concise request. If the user supplied enough detail, do not ask for confirmation before creating the task.

Record only the review rounds, verification, and approval gates required by the task or harness. Do not add repeated reviews or broad tests for low-impact changes merely to make the plan look thorough. The successful handoff's stop rule below is a runtime ownership boundary, not a discretionary approval pause.

Build the initial plan

The plan must cover the whole known objective, not just the first action. Use short unique keys such as research, implement, and verify. Put prerequisite keys in dependsOn. List concrete deliverables in expectedOutputs; at least one work item must have an expected output.

Separate requirements by kind:

  • requirement: requested behavior or deliverable.
  • constraint: boundaries such as compatibility, safety, deadline, or allowed systems.
  • acceptance_criterion: observable evidence that the task is done. At least one is required.

Record agent-made assumptions as decisions with appropriate confidence. Use a stable idempotency key for this handoff so retries cannot create duplicate tasks.

Perform the handoff

Call createTask exactly once with the complete brief and plan. The tool validates graph integrity and creates the durable task in working state.

After a successful call, stop immediately. Do not call another tool, continue the original work, or emit a follow-up chat response. Task mode owns all subsequent execution and delivery.

If creation fails validation, correct the input and retry only when the error clearly indicates that no task was created. Never create a second task to work around an uncertain result; reuse the same idempotency key.

$ARGUMENTS

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Task AI skill do?

Hand ordinary chat off to durable Task mode when the user explicitly invokes /task or requests a managed task. Complexity, progress tracking, or a need for a plan alone does not authorize a handoff; continue that work in the current chat.

Why use Task on TypingMind?

Because you install it once and use it with any model. 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 Task in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mweinbach/agent-coworker/tree/main/skills/task. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 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 Task?

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

Is the Task AI skill free?

It is published on GitHub by mweinbach. Check the repository for licensing terms. 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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