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Create Plan

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yonatangross
create-plan

Writes an implementation plan as a file artifact in the task directory (.ork/tasks/TASK/NN-plan-SLUG.md) with phases, exact file changes and runnable success criteria, so reviewers comment on the file instead of in chat. Use when a task has its research done and needs a reviewable plan before code; pair with iterate-plan for revisions and review-artifact-comments for feedback.

Overview

Publisheryonatangross
Repositoryorchestkit
Skill namecreate-plan
Stars
299
Forks
38
Bundled files
3
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Create Plan 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/yonatangross/orchestkit/tree/main/plugins/ork/skills/create-plan
  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/yonatangross/orchestkit.git /tmp/orchestkit
mkdir -p .claude/skills
cp -r /tmp/orchestkit/plugins/ork/skills/create-plan .claude/skills/create-plan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Plan 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 Create Plan 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 Create Plan 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.

create-plan

Turn what is known about a task into one plan file that a person can review line by line. The plan lives in the task directory, and comments are written into the file, so the review history stays with the plan and survives a new session.

The layout (path, file name, front matter, comment block, the "done" signal) is fixed in references/artifact-layout.md. Only scripts/artifact.mjs writes the front matter.

Steps

  1. Find the task directory. Ask for the task name if it was not given (kebab-case, one per branch, issue or lane). List what is already there:

    bash
    node "${CLAUDE_SKILL_DIR}/scripts/artifact.mjs" status --task-dir .ork/tasks/<task>

  2. Read every artifact in it in full, in NN order: research, earlier plans, and their comment blocks. Open comments on an earlier artifact are requirements unless they were resolved.

  3. Read the code the research points at. Every file the plan changes must be opened, so file paths and code in the plan are real.

  4. Write the body to a scratch file, using references/plan-template.md. Each phase is testable on its own, names the files it changes, and ends with runnable automated checks.

  5. Create the artifact through the script (never write the file directly):

    bash
    node "${CLAUDE_SKILL_DIR}/scripts/artifact.mjs" create \
  --task <task> --kind plan --slug <slug> --title "<title>" --author <your seat> --body /tmp/plan-body.md
# prints .ork/tasks/<task>/NN-plan-<slug>.md

  6. Reply with the path and stop. Ask the reviewer to comment in the file (or run /ork:review-artifact-comments after they do). Do not start implementing.

Rules

  • When documents disagree, the newest wins: plan over research over the original ask.
  • Out of scope is a section, not an afterthought: list what the plan will not do.
  • Manual checks only where a person really has to look; do not pad phases with them.
  • A second plan for the same task is a new artifact (new NN), not an edit of the old one. Revising the same plan is iterate-plan.

Related

  • /ork:iterate-plan: revise this plan from review comments, keeping every comment.
  • /ork:create-research: the research artifact this plan should read first.
  • /ork:review-artifact-comments: read, answer and resolve comments on any artifact.

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 Create Plan AI skill do?

Writes an implementation plan as a file artifact in the task directory (.ork/tasks/TASK/NN-plan-SLUG.md) with phases, exact file changes and runnable success criteria, so reviewers comment on the file instead of in chat. Use when a task has its research done and needs a reviewable plan before code; pair with iterate-plan for revisions and review-artifact-comments for feedback.

Why use Create Plan on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yonatangross/orchestkit/tree/main/plugins/ork/skills/create-plan. 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 Create Plan?

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 Create Plan?

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

Is the Create Plan AI skill free?

Yes. It is published on GitHub by yonatangross 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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