Plan

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hegemonart

plan

Stage 3 of 5 orchestrator that reads DESIGN-CONTEXT.md, runs optional research (phase-researcher / pattern-mapper / assumptions-analyzer / synthesizer), spawns design-planner + design-plan-checker, and writes DESIGN-PLAN.md. Use when DESIGN-CONTEXT.md is locked and you need a wave-ordered execution plan. Activates for requests involving breaking design work into steps, sequencing implementation, or planning a build.

Overview

Publisher	hegemonart
Repository	`get-design-done`
Skill name	`plan`
Stars	3
Forks	1
Bundled files	1
License	MIT
Links	Skill source Repository

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 hegemonart on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/hegemonart/get-design-done/tree/main/scripts/skill-templates/plan
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.

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/hegemonart/get-design-done.git /tmp/get-design-done
mkdir -p .claude/skills
cp -r /tmp/get-design-done/scripts/skill-templates/plan .claude/skills/plan

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 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 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 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.

Get Design Done - Plan

Stage 3 of 5 in the get-design-done pipeline. Thin orchestrator. All planning intelligence lives in agents/design-planner.md.

Full procedure detail: ./plan-procedure.md.

Stage entry

mcp__gdd_state__transition_stage with to: "plan". Gate failure surfaces error.context.blockers; do not advance.
mcp__gdd_state__get -> snapshot state for <position>, <connections>, <must_haves>, <blockers>, <decisions>. Do not re-read STATE.md directly.
Abort only if .design/DESIGN-CONTEXT.md is missing - that is the true prerequisite, not STATE.md.

Flags + parallelism

--auto -> auto_mode=true (skip approvals, skip optional research).
--parallel -> parallel_mode=true (planner fills Touches:/Parallel: fields).
Parallelism decision: read .design/config.json + reference/parallelism-rules.md. Plan pipeline is inherently sequential (researcher -> pattern-mapper -> planner -> checker) so the expected verdict is serial (rule 1). Record via mcp__gdd_state__update_progress with status: "plan_parallelism_decided: batch_size=<N>, reason=<short-reason>".

Probe Chromatic connection

Probe chromatic (CLI presence + CHROMATIC_PROJECT_TOKEN check; auto-unavailable if storybook: not_configured), then write status via mcp__gdd_state__probe_connections (single-entry array, never edit <connections> directly). Detail: ./plan-procedure.md §Probe Chromatic connection.

When chromatic: available, run change-risk scoping before writing DESIGN-PLAN.md: identify token/component files in scope from DESIGN-CONTEXT.md, run npx chromatic --trace-changed=expanded --dry-run, count story files that depend on changed source files, and pass the story count to the design-planner spawn prompt. Detail: ./plan-procedure.md §Chromatic Change-Risk Scoping.

Step 1 - Optional Research (skip if `auto_mode`)

Complexity heuristic: DESIGN-CONTEXT.md <domain> spans 3+ scopes OR <decisions> count > 6 -> spawn design-phase-researcher -> .design/DESIGN-RESEARCH.md (~100 lines, ~2 min). Wait for ## RESEARCH COMPLETE, then update_progress task_progress: "1/3". Full prompt: ./plan-procedure.md §Step 1.

Step 1.5 - Pattern Mapping (mandatory, brownfield protection)

Spawn design-pattern-mapper -> .design/DESIGN-PATTERNS.md (classify by design concern, not by code architecture - no controllers/services/middleware vocabulary). Wait for ## MAPPING COMPLETE. Full prompt: ./plan-procedure.md §Step 1.5.

Step 1.6 - Assumptions Analysis (skip if `auto_mode`)

If assumptions analysis is enabled: spawn design-assumptions-analyzer -> surfaces hidden design assumptions with confidence + evidence. Wait for ## ANALYSIS COMPLETE. Full prompt: ./plan-procedure.md §Step 1.6.

Step 1.7 - Synthesize pre-plan inputs (Plan 10.1-04, D-13/D-15)

If 2+ pre-plan agents ran (Step 1, 1.5, 1.6), invoke Skill("synthesize", { outputs, directive, output_shape: "markdown" }) to merge their outputs into .design/DESIGN-PREPLAN-BRIEF.md (~150 lines, per-source headers preserved). Add the brief to the planner's <required_reading> in Step 2. If only one agent ran, skip. Full call signature + parallel-synthesizer note: ./plan-procedure.md §Step 1.7.

Research-synthesis persistence: for each D-XX the synthesizer produces, mcp__gdd_state__add_decision; for each M-XX, mcp__gdd_state__add_must_have. Issue sequentially (lockfile-bound). Detail: ./plan-procedure.md §Research-synthesis persistence.

Step 2 - Plan

Spawn design-planner with <required_reading> covering STATE.md, DESIGN-CONTEXT.md, DESIGN-PATTERNS.md, plus (conditionally) DESIGN-RESEARCH.md, DESIGN-ASSUMPTIONS.md, DESIGN-PREPLAN-BRIEF.md (preferred when 1.7 ran), all .design/sketches/*/WINNER.md, all .design/spikes/*/FINDINGS.md, and all ./.claude/skills/design-*-conventions.md + ~/.claude/gdd/global-skills/*.md (project-local D-XX overrides globals). Wait for ## PLANNING COMPLETE, then update_progress task_progress: "2/3". Full prompt + conditional include syntax: ./plan-procedure.md §Step 2.

Step 3 - Check

Spawn design-plan-checker to validate DESIGN-PLAN.md against DESIGN-CONTEXT.md across 5 dimensions: requirement coverage, task completeness, wave ordering, must-have derivation, auto-mode compliance. Wait for ## PLAN CHECK COMPLETE, then update_progress task_progress: "3/3". On ## PLAN CHECK RESULT: ISSUES FOUND + BLOCKER: offer revise/accept/abort (auto_mode: auto-accept WARN, abort on BLOCKER). Full prompt + branching: ./plan-procedure.md §Step 3.

Stage exit

mcp__gdd_state__set_status -> "plan_complete".
mcp__gdd_state__checkpoint - stamps last_checkpoint and finalizes the plan stage.

The next stage (design) calls mcp__gdd_state__transition_stage on entry - this skill does NOT issue the transition itself, preserving the stage-owned-transition discipline.

After Completion

Print: plan tasks (N waves, M total tasks), files written (.design/DESIGN-PLAN.md, plus .design/DESIGN-RESEARCH.md if research ran), next step /get-design-done:design.

Spec self-review (before transition)

Run this final spec-quality pass over .design/DESIGN-PLAN.md before the plan→design transition:

Placeholder scan: no TBD / TODO / <placeholder> / lorem left in the artifact.
Internal consistency: sections don't contradict each other.
Scope check: nothing in the artifact exceeds (or silently drops) the agreed scope.
Ambiguity check: every requirement/decision is specific enough to act on without a follow-up question.

Rationalizations - Thought to Reality

The reasons an agent gives to skip planning or rush DESIGN-PLAN.md, and what each one costs:

Thought	Reality
"This change is small, I can design straight from DESIGN-CONTEXT.md."	Plan-skipped tasks blow scope per cycle telemetry; the plan gate is for the typical case, not the exception you think you're in.
"Pattern mapping is brownfield ceremony, I'll skip it."	Step 1.5 is mandatory because an unmapped brownfield is where the executor silently re-implements an existing pattern.
"The plan-checker will just rubber-stamp it, skip the spawn."	The checker's 5 dimensions (coverage, wave order, must-have derivation) catch the gaps you can't see in your own plan.
"I'll let the planner infer wave ordering at design time."	Unordered waves serialize work that could parallelize - or worse, run dependent tasks concurrently and corrupt the tree.
"Research is overkill for this scope."	The complexity heuristic exists precisely because agents under-estimate scope; skipping research on a 3+-scope domain guarantees a mid-design surprise.
"I can record decisions in DESIGN-PLAN.md prose instead of D-XX."	Prose decisions never reach STATE.md, so verify's integration-checker can't trace them and flags them orphaned.

PLAN COMPLETE

Bundled files

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

plan-procedure.md12 KB

Frequently asked questions

What does the Plan AI skill do?

Why use Plan on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hegemonart/get-design-done/tree/main/scripts/skill-templates/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 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 Plan?

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

Is the Plan AI skill free?

Yes. It is published on GitHub by hegemonart 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Get Design Done - Plan

Stage entry

Flags + parallelism

Probe Chromatic connection

Step 1 - Optional Research (skip if auto_mode)

Step 1.5 - Pattern Mapping (mandatory, brownfield protection)

Step 1.6 - Assumptions Analysis (skip if auto_mode)

Step 1.7 - Synthesize pre-plan inputs (Plan 10.1-04, D-13/D-15)

Step 2 - Plan

Step 3 - Check

Stage exit

After Completion

Spec self-review (before transition)

Rationalizations - Thought to Reality

PLAN COMPLETE

Bundled files

Frequently asked questions

Related AI Skills

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Step 1 - Optional Research (skip if `auto_mode`)

Step 1.6 - Assumptions Analysis (skip if `auto_mode`)