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First Task

OrganizationPopular
paperclipai
first-task

Guide the user's first Paperclip task when its description invokes /first-task. Interpret the opening answer, clarify their goal, propose a plan or a single task, and wait for approval before hiring agents or executing approved work.

Overview

Publisherpaperclipai
Repositorypaperclip
Skill namefirst-task
Stars
95.4K
Forks
16.2K
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 paperclipai on GitHub. Read the source before you install it.

Installation

Install the First 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/paperclipai/paperclip/tree/master/server/src/onboarding-assets/first-task/skills/first-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/paperclipai/paperclip.git /tmp/paperclip
mkdir -p .claude/skills
cp -r /tmp/paperclip/server/src/onboarding-assets/first-task/skills/first-task .claude/skills/first-task
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable First 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 First 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 First 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.

First task

Use this workflow only for the onboarding task that invokes /first-task, including later replies and approval wakes on that same task. Do not apply it to the agent's other tasks just because this skill is installed. Follow it without announcing the first-task skill in routine messages, cards, or documents. Say "I'm doing X," not "I'm using the first-task skill to do X," and explain next steps directly. This is a wording preference: answer truthfully if the user asks about the workflow, and always disclose relevant permissions, security implications, and execution actions.

This is the user's first task in Paperclip. Your job is to understand what they want and propose a path forward. A greeting and an opening question card were already posted for you; the card offered two choices: "Interview me and propose a plan and an agent team to execute it." (option interview) or "I have a task in mind" (option task, with a text field). You are running because the user answered that card (the answer is in your wake payload) or wrote a message instead of answering. Don't re-introduce yourself and don't post the opening card again.

Work in this order.

  1. Take the path the user picked.

    • interview → ask the user 3–4 questions in one Paperclip question card (request_human_input with interactionKind: "questions" when available, otherwise the ask_user_questions API) that pin down what their organization does, what they want to achieve first, any constraints (time, budget, tools), and what "done" looks like. Don't guess; ask. Don't post anything else before the card. The answers lead to the plan-and-team path in step 2.

    • task → the text they typed is the task. If it is clear enough to propose on, go straight to step 2. If not, reply by asking 2–3 questions specific to their message (concrete goal, constraints, what "done" looks like), then go to step 2.

    • If they wrote a message instead of answering the card, treat the message as the task path.

  2. Propose, then wait for acceptance.

    • Choose the proposal form from the user’s request first: an explicit plan request or the interview path always requires a saved plan, even when the task description says confirmation.
    • If they want a plan, save a plan document on this onboarding task describing the goal, scope, steps, proposed team, and what done means. Post one request_checkbox_confirmation targeting the saved plan revision. A card or thread message alone is not a saved plan. This applies to explicit plan requests regardless of the single-task proposal mode. Proposing a team does not authorize hiring it.
    • If they want one thing done, propose exactly one child task with a clear outcome and scope. Ask them to accept it before creating the child. Do not produce the requested finished work inside the proposal, even when it is quick to do.
    • For a single-task proposal, follow the Single-task proposal mode saved in the task description: confirmation means one request_confirmation card describing the child task, without a plan document; plan means save a short plan document describing that same child task and post one request_checkbox_confirmation targeting its saved revision.
    • Keep this task in_review while waiting. You may clarify, research for planning, and save or revise a plan/proposal before acceptance. Do not hire, create execution tasks, perform the deliverable, save finished output, or claim completion yet.
  3. Interpret the next reply against the latest proposal.

    • Acceptance is an accepted confirmation card or an explicit conversational reply agreeing to the proposal. The opening answer, a clear request, and answers to clarification questions supply scope; they are not acceptance of a proposal you have not yet made.
    • When acceptance or rejection arrives in chat, persist it on the corresponding pending confirmation before hiring, creating a child, executing, or closing this task. Read this task's interactions and comments, then POST /api/issues/{issueId}/interactions/{interactionId}/resolve-from-comment with { "commentId": "<user-message-id>", "decision": "accept" } (or "reject" and the user's reason). Native runners use call_api. For a checkbox card, include selectedOptionIds for the user's actual selection; never infer acceptance from defaults. Wait for the saved accepted/rejected result. Retry an interrupted write using the same message and decision; inspect a conflicting result instead of proceeding. Do not tell the user to return to the card after answering in chat.
    • An ambiguous reply with multiple pending proposals is not permission to resolve them all. Ask which proposal or options they mean. A card already answered through the UI needs no second resolution. Forms, governed actions, and human-only policies keep their existing response rules.
    • A clarification answer means update the proposal if needed and ask for acceptance. A requested revision supersedes the old scope: revise the proposal and wait for acceptance of the revised version.
    • If they reject the proposal, acknowledge and stop. Do not execute it. You may close the onboarding task after acknowledging the rejection; do not describe rejected work as completed.
  4. Carry out the accepted scope.

    • For a plan-only request, retain the accepted plan on this task. Do not start its implementation or hire the proposed team without authorization to do that work.
    • For an accepted single task, check for an existing child from this proposal before creating anything. Create exactly one child linked to this onboarding task, assign it to yourself, and execute it. On later wakes, continue that same child instead of creating another.
    • Save the finished output as a document on the child task and mark that child done. Link it from the onboarding conversation. Completing the onboarding parent in place, or saving the output only on the parent, does not fulfill the accepted child-task proposal.

Frequently asked questions

What does the First Task AI skill do?

Guide the user's first Paperclip task when its description invokes /first-task. Interpret the opening answer, clarify their goal, propose a plan or a single task, and wait for approval before hiring agents or executing approved work.

Why use First Task on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/paperclipai/paperclip/tree/master/server/src/onboarding-assets/first-task/skills/first-task. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use First 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 First Task?

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

Is the First Task AI skill free?

Yes. It is published on GitHub by paperclipai 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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