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Gdd Context

Community
hegemonart
gdd-context

Queries the typed DesignContext graph at .design/context-graph.json - the design-semantic map of tokens, components, variants, states, motion, a11y patterns, screens, layers, and design patterns plus the edges between them. Lists and filters nodes and edges, traces a path between two nodes, finds the consumers of a node, and reports unreachable nodes, dependency cycles, and coverage. Use when the user wants to inspect the design graph, find what depends on a token or component, trace how one node reaches another, or check graph health. Activates for requests involving the design context graph, design dependencies, token consumers, component composition, unreachable design nodes, design cycles, or design coverage.

Overview

Publisherhegemonart
Repositoryget-design-done
Skill namegdd-context
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 Context 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/context
  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/context .claude/skills/gdd-context
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gdd Context 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 Context 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 Context 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.

{{command_prefix}}context

Role: Read-only front end for the typed DesignContext graph. The graph is a design-semantic map: nodes are tokens, components, variants, states, motion fragments, a11y patterns, screens, layers, and design patterns; edges connect them (uses-token, composes, extends, transitions-to, depends-on, mirrors, conflicts-with, referenced-by, tested-by, documented-by, consumes-context, provides-context). This skill queries that graph. It never writes to it. The graph is authored by the mapper agents plus the design-research-synthesizer; this skill only reads.

The query engine ships at scripts/lib/design-context-query.cjs (authored elsewhere; this skill only calls it). It is pure and dep-free, exposing load, nodes, edges, path, consumersOf, unreachable, cycles, and coverage. The merged graph lives at .design/context-graph.json with the shape { schema_version, generated_at, nodes[], edges[] }.

If .design/context-graph.json is absent, print: No DesignContext graph yet. Run the design research pipeline (mappers plus {{command_prefix}}synthesize) to generate .design/context-graph.json. Then STOP. Do not invent a graph.

The engine exposes a module API rather than a CLI, so drive it from a short node -e script, the same way other skills call a scripts/lib helper:

bash
node -e "const q=require('${CLAUDE_PLUGIN_ROOT}/scripts/lib/design-context-query.cjs'); \
  const g=q.load('.design/context-graph.json'); \
  console.log(JSON.stringify(q.nodes(g, { type: process.env.NODE_TYPE || undefined, tag: process.env.TAG || undefined })));"

Invocation Modes

CommandBehavior
{{command_prefix}}context nodesList graph nodes, optionally filtered by --type and --tag (default mode).
{{command_prefix}}context edgesList graph edges, optionally filtered by --type.
{{command_prefix}}context path <a> <b>Trace a path from node <a> to node <b>.
{{command_prefix}}context consumers-of <id>List the nodes that consume node <id>.
{{command_prefix}}context unreachableList nodes no edge reaches.
{{command_prefix}}context cyclesList dependency cycles in the graph.
{{command_prefix}}context coverageReport graph coverage (typed and tagged ratios).

Output discipline: emit JSON when a tool or another skill is the caller; render a compact table when a person is at the terminal.

nodes

List nodes. --type <t> filters by node type (token, component, variant, state, motion-fragment, a11y-pattern, screen, layer, pattern, anti-pattern). --tag <tag> filters by a controlled tag. Call nodes(graph, { type, tag }):

bash
node -e "const q=require('${CLAUDE_PLUGIN_ROOT}/scripts/lib/design-context-query.cjs'); \
  const g=q.load('.design/context-graph.json'); \
  console.log(JSON.stringify(q.nodes(g, { type: process.env.NODE_TYPE || undefined, tag: process.env.TAG || undefined })));"

Render one row per node. Keep it scannable:

ID                  TYPE        COMPLEXITY  NAME
token:color/brand   token       simple      Brand primary
component:Button    component   moderate    Button

If no nodes match, say so plainly and suggest a broader filter.

edges

List edges. --type <t> filters by edge type (uses-token, composes, extends, transitions-to, depends-on, mirrors, conflicts-with, referenced-by, tested-by, documented-by, consumes-context, provides-context). Call edges(graph, { type }):

bash
node -e "const q=require('${CLAUDE_PLUGIN_ROOT}/scripts/lib/design-context-query.cjs'); \
  const g=q.load('.design/context-graph.json'); \
  console.log(JSON.stringify(q.edges(g, { type: process.env.EDGE_TYPE || undefined })));"

Render source -> target (type, weight) per row. If none match, report it and suggest dropping the filter.

path

Trace a path between two node ids. Call path(graph, from, to):

bash
node -e "const q=require('${CLAUDE_PLUGIN_ROOT}/scripts/lib/design-context-query.cjs'); \
  const g=q.load('.design/context-graph.json'); \
  console.log(JSON.stringify(q.path(g, process.env.FROM, process.env.TO)));"

Print the ordered node ids joined by arrows. If no path exists, print No path from <a> to <b>. Do not fabricate intermediate nodes.

consumers-of

List the nodes that consume a given node (the inbound side). Call consumersOf(graph, id):

bash
node -e "const q=require('${CLAUDE_PLUGIN_ROOT}/scripts/lib/design-context-query.cjs'); \
  const g=q.load('.design/context-graph.json'); \
  console.log(JSON.stringify(q.consumersOf(g, process.env.ID)));"

Render the consumer ids one per row. If the id is unknown, print No node <id> in the graph. and suggest {{command_prefix}}context nodes.

unreachable

List nodes that no edge reaches (orphans). Call unreachable(graph):

bash
node -e "const q=require('${CLAUDE_PLUGIN_ROOT}/scripts/lib/design-context-query.cjs'); \
  const g=q.load('.design/context-graph.json'); \
  console.log(JSON.stringify(q.unreachable(g)));"

If the list is empty, print Every node is reachable.

cycles

List dependency cycles. Call cycles(graph):

bash
node -e "const q=require('${CLAUDE_PLUGIN_ROOT}/scripts/lib/design-context-query.cjs'); \
  const g=q.load('.design/context-graph.json'); \
  console.log(JSON.stringify(q.cycles(g)));"

Print each cycle as its ordered node ids. If there are none, print No cycles detected.

coverage

Report graph coverage. Call coverage(graph):

bash
node -e "const q=require('${CLAUDE_PLUGIN_ROOT}/scripts/lib/design-context-query.cjs'); \
  const g=q.load('.design/context-graph.json'); \
  console.log(JSON.stringify(q.coverage(g)));"

Surface the returned ratios (for example typed and tagged coverage and node and edge counts) as a short summary.

Do Not

  • Do not edit .design/context-graph.json or the fragments under .design/fragments/. All writes go through the mapper agents and the synthesizer.
  • Do not invent nodes, edges, or paths. If a query returns nothing, report it plainly.
  • Do not modify scripts/lib/design-context-query.cjs or the DesignContext schema.

CONTEXT COMPLETE

Frequently asked questions

What does the Gdd Context AI skill do?

Queries the typed DesignContext graph at .design/context-graph.json - the design-semantic map of tokens, components, variants, states, motion, a11y patterns, screens, layers, and design patterns plus the edges between them. Lists and filters nodes and edges, traces a path between two nodes, finds the consumers of a node, and reports unreachable nodes, dependency cycles, and coverage. Use when the user wants to inspect the design graph, find what depends on a token or component, trace how one node reaches another, or check graph health. Activates for requests involving the design context gra...

Why use Gdd Context on TypingMind?

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

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

Which AI models can use Gdd Context?

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 Context?

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

Is the Gdd Context 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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