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Interaction Design Board

CommunityPopular
daymade
interaction-design-board

Generate several genuinely different, runnable HTML interaction prototypes for one product surface, combine them in an interactive Design Board, collect structured selection/remix feedback, and only then hand the approved behavior to production implementation. Use when a user asks for multiple clickable UI versions, interaction alternatives, progressive-disclosure options, a Design Board, HTML prototypes, test-time scaling for product design, or says the visual styling is acceptable but the hierarchy, workflow, layout, or interaction still feels unprofessional. Prefer this over static image exploration when the decision depends on what happens after clicking, expanding, selecting, filtering, or moving through states.

Overview

Publisherdaymade
Repositoryclaude-code-skills
Skill nameinteraction-design-board
Stars
1.4K
Forks
219
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

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

Installation

Install the Interaction Design Board 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.
  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/daymade/claude-code-skills.git /tmp/claude-code-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-skills/daymade-codex/interaction-design-board .claude/skills/interaction-design-board
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Interaction Design Board 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 Interaction Design Board 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 Interaction Design Board 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.

Interaction Design Board

Turn interaction uncertainty into inspectable evidence. Keep the product's real facts and design language fixed; vary the interaction architecture enough that the user can experience the trade-offs before production code changes.

Route The Request

  • Use this skill when the choice depends on behavior, state, workflow, hierarchy, or progressive disclosure.
  • Use design-style-picker for static visual-style calibration and image matrices.
  • Use gstack's design-consultation for a new product-wide design system and gstack's design-shotgun for static generated mockups.
  • Return to this skill after a visual direction is chosen if the user still needs to compare clickable interaction structures.
  • Do not use it for a settled one-line CSS adjustment or when the user already supplied an approved interaction specification and asked only for implementation.

Non-Negotiable Outcome

Produce a decision, not a gallery:

  1. Several runnable HTML candidates keep the same business facts, product scope, design tokens, and available actions.
  2. Each candidate embodies a distinct interaction hypothesis rather than a skin.
  3. The Design Board lets the user operate every candidate, record concrete feedback, select one, or request a named remix.
  4. Production implementation does not start until the user approves the behavior.

Static screenshots are supporting evidence only. A screenshot cannot prove a collapse state, keyboard path, selection model, or task handoff.

Workflow

1. Freeze The Decision Contract

Before generating variants, write a compact contract in the session workspace:

  • User job: the real task the operator is trying to complete.
  • Decision scope: the one page, component, or bounded journey being compared.
  • Immutable facts: real objects, labels, statuses, permissions, actions, and data semantics that every variant must preserve.
  • Existing language: current tokens, components, navigation, density, and brand assets that must remain recognizable.
  • First-view invariant: what must stay visible before any disclosure.
  • Interaction states: the meaningful states the user must be able to exercise.
  • Stop condition: approved variant or explicit remix brief; no product edit yet.

For an existing product, inspect its rendered page and implementation before writing the contract. Do not replace unknown facts with plausible sample data. Mark unknowns as unknown or omit them if they are not needed for the interaction choice.

Read references/interaction-design-method.md before proposing the candidate architectures. It contains the hierarchy, progressive-disclosure, comparison, and accessibility rules that decide whether a direction is legitimate.

2. Propose Different Interaction Architectures

Propose three candidates by default. Add candidates only when another independent interaction hypothesis exists; do not inflate the board with minor variants.

For each candidate state:

  • the hypothesis about how it helps the user's job;
  • what it makes primary;
  • what it defers or hides;
  • the likely trade-off;
  • the states and actions that must work in the prototype.

Hold the decision contract constant. Change navigation/selection/disclosure/action ownership or information order—not colors, copy, and data all at once. Useful families include command-first, queue-detail, object-led, comparison-led, and ledger-first, but derive candidates from the current task rather than filling a pattern quota.

3. Generate Isolated Runnable Candidates

Create one self-contained HTML file per candidate in a session workspace outside the product source tree. Keep CSS and JavaScript inline; avoid runtime network dependencies so every prototype survives inside the Board.

When independent worker contexts are available, assign one candidate to each worker with the same frozen decision contract and only that candidate's hypothesis. Do not let workers see one another's output. This isolation is the test-time-scaling mechanism: it preserves distinct hypotheses instead of converging into siblings. If workers are unavailable, generate serially but re-read the frozen contract—not the previous candidate—before starting the next one.

Each candidate must implement the declared states. Decorative buttons that do nothing are not interaction prototypes. Use honest local state; do not simulate a backend response the product does not have.

4. Build And Open The Design Board

Create board.json using references/board-contract.md, then run:

bash
SKILL_ROOT="<absolute directory containing this loaded SKILL.md>"
python3 "$SKILL_ROOT/scripts/build_board.py" \
  --manifest <session-dir>/board.json \
  --output <session-dir>/design-board.html

Expected output:

text
BOARD_BUILT variants=<derived count> output=<absolute path>

The builder rejects byte-identical candidates, path traversal, missing declared states, and static external styles, scripts, or media. The Board also injects a network-denying Content Security Policy into every sandboxed candidate so dynamic JavaScript cannot create an undeclared runtime dependency. Fix the candidate; do not weaken either boundary to make the Board green.

If gstack's design executable is already installed, resolve its absolute path from the active gstack Skill installation; do not assume $D exists in a new shell. Then capture the exact Board URL printed by the server:

bash
GSTACK_DESIGN="<resolved gstack design executable>"
SERVER_OUTPUT="$("$GSTACK_DESIGN" serve \
  --html <session-dir>/design-board.html --timeout 1800 2>&1)"
printf '%s\n' "$SERVER_OUTPUT"
BOARD_URL="$(printf '%s\n' "$SERVER_OUTPUT" | sed -n 's/^BOARD_URL: //p' | tail -1)"
test -n "$BOARD_URL"

If the executable cannot be resolved or the command prints no BOARD_URL, open design-board.html directly with the host's browser-opening tool. Direct-file mode remains functional: Submit and Remix download feedback.json or feedback-pending.json for the agent to read. The Board itself is the chooser; chat is only the fallback channel.

5. Observe Tasks, Not Vibes

Ask the user to operate the same representative task in every candidate. Record:

  • what they noticed first;
  • where they knew or did not know what to do next;
  • which disclosure helped or hid necessary evidence;
  • which state transition felt natural or surprising;
  • which elements to preserve, reject, or remix.

Do not replace these observations with a numeric score or a claim that the most polished candidate is best. The user may choose one candidate or combine named parts of several.

When feedback-pending.json appears, preserve the accepted parts, alter the named failure axis, regenerate only the affected candidates, and build a versioned Board file in the same session directory. If a gstack Board is already serving, reload that exact Board instead of calling serve again on the old source path:

bash
curl -sS -X POST "${BOARD_URL%/}/api/reload" \
  -H 'Content-Type: application/json' \
  -d '{"html":"<absolute-versioned-board-path>"}'

Expected response: {"reloaded":true}. Repeated serve calls may reuse a Board instance without reading changed bytes, so they are not a reload mechanism. Ask the user to retry the task in the same Board URL. Stop adding rounds when feedback no longer changes the decision.

6. Freeze Approval Before Production

After the user confirms your feedback summary, write approved.json beside the Board using the schema in references/board-contract.md. Capture:

  • selected or remixed candidate;
  • approved interaction rules and first-view invariant;
  • rejected trade-offs;
  • states the user actually exercised;
  • remaining unknowns;
  • exact prototype file identities.

Then—and only then—implement in the product. Preserve the current design system and real data contracts. Use the project's frontend implementation and visual-QA skills, then verify the same representative task in the real browser. Pixel resemblance is insufficient; the approved state transitions and information order must survive.

If the project has a design SSOT, write the approved interaction decision there as part of implementation. Keep session feedback and prototype files as evidence; do not copy their changing values into general project instructions.

Failure Boundaries

  • Do not turn every candidate into a different product or data model.
  • Do not let static image generation stand in for runnable interaction.
  • Do not hide identity, current status, primary evidence, or the next action behind progressive disclosure when they are necessary to decide.
  • Do not implement the apparent winner before the user has operated it.
  • Do not write prototypes into production component directories.
  • Do not claim usability validation from the author's own click-through. Agent QA catches broken states; the user's task observation decides the interaction.

Delivery

Return the Board path or URL, candidate hypotheses, feedback/approval artifact paths, browser verification performed, and the explicit next step: iterate the Board, implement the approved candidate, or stop.

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 Interaction Design Board AI skill do?

Generate several genuinely different, runnable HTML interaction prototypes for one product surface, combine them in an interactive Design Board, collect structured selection/remix feedback, and only then hand the approved behavior to production implementation. Use when a user asks for multiple clickable UI versions, interaction alternatives, progressive-disclosure options, a Design Board, HTML prototypes, test-time scaling for product design, or says the visual styling is acceptable but the hierarchy, workflow, layout, or interaction still feels unprofessional. Prefer this over static image...

Why use Interaction Design Board on TypingMind?

Because you install it once and use it with any model. Interaction Design Board 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 Interaction Design Board in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/daymade/claude-code-skills/tree/main/daymade-codex/interaction-design-board. 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 Interaction Design Board?

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 Interaction Design Board?

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

Is the Interaction Design Board AI skill free?

Yes. It is published on GitHub by daymade 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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