Memoire Design Tooling

Organization

memi-design

memoire-design-tooling

Use when an OpenClaw workspace task involves UI design, interface craft, Figma, design systems, shadcn/ui, Tailwind, Atomic Design, research synthesis, design audits, component specs, or code generation from design evidence.

Overview

Publisher	memi-design
Repository	`memi`
Skill name	`memoire-design-tooling`
Stars	49
Forks	6
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 memi-design on GitHub. Read the source before you install it.

Installation

Install the Memoire Design Tooling 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/memi-design/memi/tree/main/agent-kits/mirror/openclaw/memoire-design-tooling
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/memi-design/memi/tree/main/agent-kits/mirror/openclaw/memoire-design-tooling

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/memi-design/memi.git /tmp/memi
mkdir -p .claude/skills
cp -r /tmp/memi/agent-kits/mirror/openclaw/memoire-design-tooling .claude/skills/memoire-design-tooling

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

Use it in TypingMind

Enable Memoire Design Tooling 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 Memoire Design Tooling 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 Memoire Design Tooling 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.

Memi Design Tooling

Memi gives coding agents repository-specific interface evidence before they edit UI. Start with the smallest workflow that answers the task; Figma, global installation, and a daemon are optional.

Choose A Workflow

Before reviewing or changing frontend UI: use audit-frontend-design.
Before building from an existing product system: use remember-design-system.
When adding deterministic pull-request gates: use enforce-design-ci.
For native SwiftUI, SwiftData, App Intents, or Apple-platform verification: use build-swiftui-interface.
For Figma, research, scaffolding, registry publishing, or multi-agent work: continue below.

Install one focused skill directly:

bash
npx skills add memi-design/memi --skill audit-frontend-design

This skill requires the reviewed 2.8 frontend contract. Check memi --version and npm registry availability first. If the beta is unpublished, use a reviewed local build; after publication, use the exact verified beta version. npm stable remains 2.7.9.

Compact Preflight

bash
memi agent brief . --frontend --intent "<interface task>" --max-bytes 16384 --json

Read cited source files when the bounded brief lacks necessary evidence. Optional --design-evidence design/selected-node.json accepts normalized Figma/Paper data supplied by the harness; missing mappings and verification stay explicit.

Local Checks And MCP

bash
memi diagnose . --json --no-write --fail-on none
memi diagnose . --receipt-only --fail-on none
memi --profile locked mcp start --no-figma

Locked MCP exposes four read tools: prepare_frontend_brief, prepare_design_agent_brief, prepare_apple_design_brief, and diagnose_app_quality. The frontend tool supplies actual repository evidence. Many legacy CLI and write tools remain unavailable; capability grants do not unlock deferred command paths. Keep connector calls, project edits, and browser execution in the harness's reviewed workflow.

Reuse local components and tokens according to the consumer project's conventions. Source-bearing JSON is working context; receipt-only is a separate metadata output. See docs/FRONTEND_WORKFLOW.md for the candidate evidence schema and actual verification flow.

Evidence Contract

Read local instructions and existing product-system files first.
Collect the minimum evidence that can change the implementation.
Cite file:line findings and existing components or tokens.
Make scoped edits.
Re-run the same deterministic checks.
Report commands, artifacts, files changed, and remaining assumptions.

Do not claim visual correctness from source checks alone. When rendered behavior matters, verify the actual route at desktop and mobile viewports.

Frequently asked questions

What does the Memoire Design Tooling AI skill do?

Why use Memoire Design Tooling on TypingMind?

Because you install it once and use it with any model. Memoire Design Tooling 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 Memoire Design Tooling in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/memi-design/memi/tree/main/agent-kits/mirror/openclaw/memoire-design-tooling. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Memoire Design Tooling?

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 Memoire Design Tooling?

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

Is the Memoire Design Tooling AI skill free?

Yes. It is published on GitHub by memi-design 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

Memi Design Tooling

Choose A Workflow

Compact Preflight

Local Checks And MCP

Evidence Contract

Frequently asked questions

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