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Gdd Map

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hegemonart
gdd-map

Dispatches 5 specialist codebase mappers in parallel. Produces .design/map/*.md files consumed by the explore stage.

Overview

Publisherhegemonart
Repositoryget-design-done
Skill namegdd-map
Stars
3
Forks
1
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 hegemonart on GitHub. Read the source before you install it.

Installation

Install the Gdd Map 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/hegemonart/get-design-done/tree/main/scripts/skill-templates/map
  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/hegemonart/get-design-done.git /tmp/get-design-done
mkdir -p .claude/skills
cp -r /tmp/get-design-done/scripts/skill-templates/map .claude/skills/gdd-map
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gdd Map 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 Gdd Map 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 Gdd Map 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 - Map

Parallel orchestrator. Spawns 5 specialist mappers, each writing one file under .design/map/. The explore stage consumes these when present. See ./reference/heuristics.md §"Optimization rules" for parallel-spawn cost considerations.

Mapper → Output

MapperOutput
token-mapper.design/map/tokens.md
component-taxonomy-mapper.design/map/components.md
visual-hierarchy-mapper.design/map/visual-hierarchy.md
a11y-mapper.design/map/a11y.md
motion-mapper.design/map/motion.md

Step 1 - Setup

  • Ensure .design/map/ exists (create if missing).
  • Read .design/config.json → parallelism object. Use reference/config-schema.md defaults if absent.
  • Read .design/STATE.md - note <connections> (Figma availability for token-mapper).
  • Parse $ARGUMENTS. If --only <name>, restrict the dispatch set to one mapper.

Step 2 - Parallelism Decision

Per reference/parallelism-rules.md: all 5 mappers have parallel-safe: auto with disjoint writes: (each writes a different .design/map/*.md file) - no hard-rule conflict. typical-duration-seconds sum (~210s) minus slowest (~45s) ≈ 165s savings → clears min_estimated_savings_seconds. Verdict: parallel.

Write the verdict to STATE.md:

xml
<parallelism_decision>
  stage: map
  verdict: parallel
  reason: "5 mappers, parallel-safe: auto, writes disjoint, est savings ~165s"
  agents: ["token-mapper", "component-taxonomy-mapper", "visual-hierarchy-mapper", "a11y-mapper", "motion-mapper"]
  ruled_out: []
  timestamp: [ISO 8601 now]
</parallelism_decision>

--only → adjust agents and set verdict: serial with reason: "single mapper requested".

Step 3 - Dispatch (concurrent)

Spawn all selected mappers in a single response with multiple Task() calls:

Task("<mapper-name>", """
<required_reading>
@.design/STATE.md
@reference/audit-scoring.md
[@reference/accessibility.md — a11y-mapper only]
[@reference/motion.md — motion-mapper only]
</required_reading>

You are <mapper-name>. Scan the codebase per your agent spec and write your
output file under .design/map/. Emit your completion marker when done.
""")

Wait for each completion marker: ## TOKEN MAP COMPLETE, ## COMPONENT MAP COMPLETE, ## VISUAL HIERARCHY MAP COMPLETE, ## A11Y MAP COMPLETE, ## MOTION MAP COMPLETE.

Step 3.5 - Synthesize parallel mapper outputs (Plan 10.1-04, D-13/D-14/D-15)

Each mapper has written its own .design/map/*.md (disjoint writes). Main-context doesn't need all 5 verbatim - invoke synthesize inline with outputs:[<each file's text labelled "=== from <mapper> ==="], directive: "Merge into cross-cutting DESIGN-PATTERNS.md preserving section headers; consolidate cross-mapper duplicates with source-agent names; target ~120 lines.", output_shape:"markdown".

Wait for ## SYNTHESIS COMPLETE. Write merged markdown to .design/DESIGN-PATTERNS.md (overwrite if present) - the primary explore-stage input; per-mapper files remain as drill-down evidence. --only (single mapper) → skip this step.

Step 4 - Collate

Write .design/DESIGN-MAP.md - thin index linking to each .design/map/*.md with a one-paragraph summary from each file's header. If Step 3.5 ran, also cross-link to .design/DESIGN-PATTERNS.md and note at the top: "See DESIGN-PATTERNS.md for the merged cross-cutting summary - this index preserves per-mapper drill-down."

Step 5 - Report

━━━ Map complete ━━━
Files: .design/map/tokens.md, components.md, visual-hierarchy.md, a11y.md, motion.md
Index: .design/DESIGN-MAP.md
Next: {{command_prefix}}explore (consumes .design/DESIGN-PATTERNS.md on happy path; .design/map/*.md available for drill-down)
━━━━━━━━━━━━━━━━━━━━━

MAP COMPLETE

Frequently asked questions

What does the Gdd Map AI skill do?

Dispatches 5 specialist codebase mappers in parallel. Produces .design/map/*.md files consumed by the explore stage.

Why use Gdd Map on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hegemonart/get-design-done/tree/main/scripts/skill-templates/map. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gdd Map?

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 Gdd Map?

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

Is the Gdd Map 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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