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Plan Page

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udecode
plan-page

Write, check, repair and publish a plan page: a project's plans and subject files under its plans directory, rendered by .agents/pstack/plan-page.mjs and rendered as one local HTML page per subject with a local index of every subject, and published to claude.ai at each hand-back for comments and feedback. The page is how work hands back to the user. Use before writing or changing a plan, a subject file in <plans>/topics or its page; at every stop that hands work back, such as a review verdict other than a review-only panel's, a next answer or a playbook's close; when a plan page or its claude.ai artifact looks wrong or refuses to render; to republish a page; or to change the page shape or a playbook's page sections.

Overview

Publisherudecode
Repositorydotai
Skill nameplan-page
Stars
1.2K
Forks
82
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 udecode on GitHub. Read the source before you install it.

Installation

Install the Plan Page 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/udecode/dotai/tree/main/skills/plan-page
  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/udecode/dotai.git /tmp/dotai
mkdir -p .claude/skills
cp -r /tmp/dotai/skills/plan-page .claude/skills/plan-page
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plan Page 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 Plan Page 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 Plan Page 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.

Plan page

The user reads pages, not replies; the block's Plan pages rule says when to publish and what the reply holds. A subject is one thing the work changes, and it has one page. Its file, <plans>/topics/<slug>.md, holds the current state. Each plan that continues it is an iteration carrying only its delta. node .agents/pstack/plan-page.mjs <plan> renders the page from both into <plans>/artifacts/, a local copy that regenerates from the committed plan and subject files, which are the record. node .agents/pstack/plan-page.mjs --index renders every subject's page there and an index linking them. A published claude.ai page is where the user comments on one hand-back; it is not the record. sync-pstack ships that renderer and status.mjs into every project it manages.

Read references/shape.md before writing a plan or a subject file. It holds every file shape, the page order and the renderer's refusals.

ModeUse it to
Renderpublish a page at every stop the block's Plan pages rule lists
Checkaudit a plan and its subject before handing the page back
Repairfix a page whose shape is wrong
Changechange the page shape, the renderer, or a playbook's page sections

Render

  1. Pick the subject before writing the plan. Continue the subject whose thing the work changes. Start a new one only for a new thing that will be revisited. A one-off plan, such as a single fix or check, has no subject and keeps its own page. A stop with no plan yet, such as a review verdict or a close of work that wrote none, writes one now, either the iteration that later stops continue or a one-off plan.
  2. Name the subject with Topic: <slug> under Status:, or through the first entry of the frontmatter list the project names in pageTopic.field, so list the scope that owns the change first. A plan whose list-named subject has no file yet keeps its own page until someone creates that file; the renderer refuses a Topic: line whose subject has no file until that file exists.
  3. When a project playbook in .agents/playbooks/ writes the plan, name it with Playbook: <name> under Status:, so its page sections lead and its required sections apply. Otherwise leave the line out; the renderer refuses a name with no playbook file.
  4. Walk Check's reading list before the first publish and after each revision, then run node .agents/pstack/plan-page.mjs <plan>. It refuses every shape it can check and names the fix. Fix the plan or the subject file, never the HTML.
  5. At a close, write the plan's ## Close before rendering: what landed, the proof and its limits, the counts the block's Todo list and close rule requires, reversals and deviations first, and open work with owners.
  6. Publish the printed file with the Artifact tool to the subject's Page: URL, or to the one-off plan's own, so the user can comment on it. The first publish writes Page: <url> under the subject file's title, or under a one-off plan's Status: line. When that link no longer opens, because the page was deleted or belongs to another account, publish a new page and replace the line. The block's Plan pages rule says what the reply holds and what a Codex session does instead.
  7. After a subject page renders, run node .agents/pstack/plan-page.mjs --index, which renders every subject's page and the index locally. The index is never published.

Check

Run node .agents/pstack/plan-page.mjs <plan> --check. It runs every refusal and writes nothing. Then read the plan and its subject for what the renderer cannot judge:

  • Each before fence is a real call site at the commit before the plan, and its after fence the same call in the checkout, or the planned call while the plan is unbuilt. Each fence names its path in a comment, with one sentence above the pair.
  • While the plan is open, the subject file shows the state before it. That holds for a subject the plan created too.
  • Every subject section the plan changes carries a Delta table keyed to the subject's rows. Otherwise the page marks the section unchanged.
  • Main changes lists only non-public changes that alter how the code works.
  • Status: is one short line: the state word, then what the plan waits on. Open items go in their own section, each with its owner and where it is tracked.

Repair

  1. Copy each file to scratch before rewriting it, and keep the copy as the must-refuse fixture for any refusal that should have caught it.
  2. Run Check and fix each finding at its source. A subject that shows a plan's delta while its steps are all closed and its proof done is a finished fold whose Status: was not flipped yet; flip it instead of restoring. For an early fold, restore the subject file to its state before the open plan from the plan's before fences and git show <base>:<path>, and move the delta into the plan.
  3. Log one decision-log row for the repair.
  4. A ledger record that binds the plan's bytes goes stale on the edit. Rebind it by the project's record rule.
  5. Render and republish to the same URL.

Change

The renderer source is skills/sync-pstack/assets/pstack/plan-page.mjs in the dotai checkout, with status.mjs beside it. Its tests are the plan-page tests in skills/sync-pstack/scripts/sync-pstack.test.mjs. A section that only one project's plans write belongs in that project's playbook frontmatter, never in the renderer.

Run sync-pstack's Lesson mode, which owns the gates, the corpus rules and the delivery. This mode adds the renderer's specifics inside its steps:

  1. In Lesson step 2, when another session holds uncommitted edits in the dotai checkout, edit in a detached worktree at origin/main instead, and rebase onto their commit before each panel round, each proof and the dotai commit.
  2. In Lesson step 3, give each new refusal or behavior a test that fails on the old renderer for its named defect. A refusal that compares text gets one must-pass and one must-refuse case on each axis before any panel: case, indentation, spacing inside literals, punctuation-only lines, line order, partial overlap with another iteration and a missing section.
  3. In Lesson step 4, copy each managed project's plans, subject files, hubs, .agents/pstack.json and playbooks to scratch once, for the old renderer, then cp -R that copy and apply the change's migration to it for the new one, and diff the two plan lists before any body. When the live trees hold no instance of a state a refusal gates, also replay subject files at past commits where an iteration was open, and the scratch copies Repair kept. Give a renderer that predates --check an adapter that exits before it writes. Run both over every plan, list each newly refused plan with its owner, then render every plan with both and diff the bodies, ignoring the Updated line.
  4. Also in Lesson step 4, render one real plan in each mode the renderer branches on: a one-off plan, a subject with an open iteration and a subject with none. Use a scratch copy with its Status: flipped when no live subject is in a mode. Publish both versions for the owner to compare.

Playbook sections

A project playbook in .agents/playbooks/<name>.md names the review sections its plans write, as comma lists in its frontmatter beside extends and when:

yaml
page-lead: What other editors do, Layer and owner
page-pairs: Document shape
page-require: What other editors do
  • page-lead sections render right after Public API, the leading plan's playbook first.
  • page-pairs sections hold before and after pairs, like Public API.
  • page-require sections must exist in the subject file or its open plan whenever the project's pageTopic.hub file exists for that subject.

When the leading plan names no playbook, every playbook's sections and requirements apply. The playbook, or the skill it names, defines what each section holds.

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 Plan Page AI skill do?

Write, check, repair and publish a plan page: a project's plans and subject files under its plans directory, rendered by .agents/pstack/plan-page.mjs and rendered as one local HTML page per subject with a local index of every subject, and published to claude.ai at each hand-back for comments and feedback. The page is how work hands back to the user. Use before writing or changing a plan, a subject file in <plans>/topics or its page; at every stop that hands work back, such as a review verdict other than a review-only panel's, a next answer or a playbook's close; when a plan page or its clau...

Why use Plan Page on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/udecode/dotai/tree/main/skills/plan-page. 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 Plan Page?

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 Plan Page?

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

Is the Plan Page AI skill free?

It is published on GitHub by udecode. 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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