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Ui Picker

Community
Bandersnatch0x
ui-picker

UI shell and component semantics. Use when building a product page (list, dashboard, settings, detail, agent-admin), or when the wrong template and Badge-Tag pairing is about to be coded.

Overview

PublisherBandersnatch0x
Repositorydesign-playbook
Skill nameui-picker
Stars
3
Forks
0
Bundled files
5
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 Bandersnatch0x on GitHub. Read the source before you install it.

Installation

Install the Ui Picker 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/Bandersnatch0x/design-playbook/tree/main/packages/design-playbook/skills/ui-picker
  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/Bandersnatch0x/design-playbook.git /tmp/design-playbook
mkdir -p .claude/skills
cp -r /tmp/design-playbook/packages/design-playbook/skills/ui-picker .claude/skills/ui-picker
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ui Picker 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 Ui Picker 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 Ui Picker 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.

ui-picker

Before code: map the job to a template (shell) and component semantics. Appearance follows meaning.

Steps

1. Density + scene

Choose density (console-tight vs marketing-loose) and scene class (list / detail / settings / dashboard / editor / agent-admin / …).

When a verified .scratch/<run>/design-baseline/state.json binds a baseline (status: ready from design_baseline.verify), read that binding path first (baseline.path, usually DESIGN.md or .stitch/DESIGN.md). It is the project-specific authority for atmosphere, visual roles, density, layout, motion, and component conventions. Preserve it unless the requested change explicitly revises the baseline.

Collect read-only component candidates from two sources, in this order:

  1. observed component paths in a verified baseline's ## Component Stylings declaration, when that declaration exists;
  2. non-duplicate paths from run-local design-baseline/evidence.json components, when that file exists.

Use the second source when it is present, including waived or draft runs that never produced a status: ready binding. Those paths remain candidates only; they never substitute for a ready baseline or become design authority.

When .scratch/<run>/reference/contract.md exists (ADR-0011), read its Visual cues for ui-picker, Keep and Change, and Do not copy / exclusions. Use them as input for density, scene, region weight, and risks, never as hex tokens or as a license to copy brand chrome.

Done when: one scene label and one density choice are explicit. A bound baseline is cited by path + SHA-256. If a reference contract exists, the decision report's risks or exclusions surface its Do not copy / brand risks (path citation is enough).

2. Template

Read references/template.md. Assign main / side / action / status regions.

Done when: each region maps to a duty from spec L2 (or a stated gap in the spec).

3. Components

Read references/components.md. For each field and action, pick by role (status vs category vs confirm vs detail).

For each material role, match the candidate list against source evidence and repository conventions. Then record one of these outcomes inside the existing components: value in the decision report:

  • reuse <path> (<one-line matching reason>) when the declared component fits;
  • extend <path> (<one-line missing-variant reason>) when it is close but needs a documented variant. Or
  • new (<one-line gap reason>) when no trustworthy candidate exists.

Include the candidate path in the value when one exists. A weak or missing candidate takes the explicit new path. Do not invent a reuse claim. Do not edit, move, publish, extract, or commit a component during this step, and do not add a new top-level decision-report key or component repository.

Load only if needed:

Done when: every primary datum and action has a named component role. Each material role records reuse, extend, or new inside components: with a candidate path or an explicit gap reason. Easy-mix pairs (Badge and Tag, Dialog and Drawer, Dropdown, Menu, and Command) are resolved in writing.

4. Decision report

Write, then wait for confirmation if the user is in the loop:

text
design-baseline: <binding.path> sha256:<digest> | waived:<reason>
scene:
density:
template:
regions: …
components: primary-action -> reuse src/ui/Button.tsx (matching primary variant); status -> extend src/ui/Badge.tsx (needs warning state); empty-state -> new (no declared candidate)
baseline-changes: none | <explicitly approved change>
risks: …

baseline-changes: none tolerates a trailing same-line note (the machine face reads the none value token). Substantive commentary goes on its own line instead.

Done when: the report exists, records the bound baseline or explicit waiver, and coding has not started without it. Machine check right after writing the report: python scripts/g10_design_decisions.py .scratch/<run>/decision-report.md, do not wait for the end-of-run validate_run.py sweep.

DD entry blocks (append after the top block)

The top block above is the Fill consumption face and stays byte-identical. When a choice needs a record a reviewer could challenge, append versioned DD entry blocks after it (## DD-0001, <question> + one yaml field block each. Format and gate rules in references/decisions.md). Tier every recorded decision first:

TierTriggerWho decidesRecording duty
record (R)single reasonable choice, or local implementation inside confirmed declarationsagentone-line rationale + constraint reference
compare (C)2-3 substantive candidates inside the baseline, no E criterion hitagentcandidates + comparison axes + trade-off + rejection reasons
explore (E)any E criterion: identity drift from the bound baseline, region and weight re-composition, a T3 route from shaping, an R3 challenge, or a baseline conflictuserfull entry + user confirmation

Every compare or explore entry answers the Anti-default check with brief-specific facts inside the entry. Ask "is this the direction I would produce for any similar brief?" Signals and the dated default observations live in DECIDE-01@1 (../design-playbook/references/rules.md). Record-tier entries and point-fix runs are exempt. An explore entry's rationale also names the direction's Memorable element, the one thing this direction is remembered by.

Baseline-internal small choices never trigger full exploration. E-tier confirmation rides the preview transaction when the adapter is present (options = candidate labels, report_ref = this report; link the entry to the transaction decision_id). When absent, record kind: user + report-batch in the entry's confirmation block. R3 challenges revise by a new entry that supersedes the retired one, history is never rewritten. scripts/g10_design_decisions.py (G10, via validate_run.py) checks the machine face.

Branch, structure still open

If template is underdetermined, offer 2–3 IA variants (same spec, different main-region weight), one-line tradeoff each, pick one, then complete step 4. This branch is the C tier above: record it as a tier: compare DD entry instead of leaving the trade-off in conversation only.

Defaults that hold

  • Brand color as token and role, not a hex literal.
  • Easy-mix pair semantics and shell prohibition rules live in references/components.md and references/template.md, resolve against those tables, not from memory.

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 Ui Picker AI skill do?

UI shell and component semantics. Use when building a product page (list, dashboard, settings, detail, agent-admin), or when the wrong template and Badge-Tag pairing is about to be coded.

Why use Ui Picker on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Bandersnatch0x/design-playbook/tree/main/packages/design-playbook/skills/ui-picker. 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 Ui Picker?

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 Ui Picker?

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

Is the Ui Picker AI skill free?

It is published on GitHub by Bandersnatch0x. Check the repository for licensing terms. 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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