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Rudder Ui Polish Maintainer

Community
Undertone0809
rudder-ui-polish-maintainer

Use when implementing screenshot-driven or narrow Rudder UI polish: density, alignment, spacing, labels, cards, menus, hover states, empty states, onboarding steps, redundant pages, compact workflows, screenshots, or small visible interaction fixes.

Overview

PublisherUndertone0809
Repositoryrudder
Skill namerudder-ui-polish-maintainer
Stars
290
Forks
31
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

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

  • Open source

    Published by Undertone0809 on GitHub. Read the source before you install it.

Installation

Install the Rudder Ui Polish Maintainer 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/Undertone0809/rudder.git /tmp/rudder
mkdir -p .claude/skills
cp -r /tmp/rudder/agent-skills-bak/maintainer/rudder-ui-polish-maintainer .claude/skills/rudder-ui-polish-maintainer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rudder Ui Polish Maintainer 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 Rudder Ui Polish Maintainer 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 Rudder Ui Polish Maintainer 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.

Rudder UI Polish Maintainer

Use this skill to turn concrete Rudder UI feedback into a scoped, implemented, validated, and committed change.

The goal is not a full redesign. The goal is to preserve Rudder's dense, operator-focused interface while fixing the specific visual or interaction problem the user noticed.

Use When

Use this skill for Rudder UI tasks such as:

  • screenshot-driven visual polish
  • alignment, line-height, spacing, density, overflow, or hover fixes
  • adding a small status badge, label, icon, menu, or affordance
  • simplifying settings sections or redundant explanatory copy
  • removing a page or route that no longer belongs in the product
  • changing an empty state, onboarding step, tutorial jump, or small workflow surface
  • producing a quick screenshot of the current UI after a local change
  • explaining why a visible surface looks wrong when the user asks "为什么" and the likely answer is current CSS/layout/data layering rather than an approved implementation request

Use build-advisor first when the user explicitly asks "你懂我要怎么改吗", "先说说", or otherwise wants the product/design direction before edits. After the direction is accepted, continue here for implementation.

Use advisor-review-loop-maintainer instead when the user asks for reviewer agents, two rounds, proposal review, or an acceptance gate before handoff.

When the user invokes advisor-review-loop-maintainer for a small visible fix but only asks to "修一下", "优化一下", "去掉这个 button", "颜色不对", or similar, treat this skill as the implementation contract after a short advisor check. Say explicitly in the handoff that the work used a lightweight route rather than a full two-reviewer loop.

Do Not Use When

Do not use this skill for:

  • broad architecture refactors or large feature builds
  • pure code review with no UI change
  • data diagnosis where the core question is "why is this page empty"; use rudder-data-path-diagnostician-maintainer
  • screenshot/demo data creation; use mock-data-maintainer and then landing-proof-shots-maintainer when needed
  • release, CI, Desktop packaging, or browser automation infrastructure issues
  • UI Lab, component inventory, component fixture coverage, or design-system catalog work where the main deliverable is coverage and classification rather than a narrow rendered-state polish fix; route through development-lifecycle-router-maintainer first

Default Workflow

1. Resolve intent and mode

Classify the prompt before editing:

  • advice-only: user asks to discuss, judge, or generate options.
  • explain-only: user asks why a visual state looks the way it does, without asking to change it yet.
  • implement: user asks to fix, optimize, remove, add, or "改一下".
  • screenshot: user wants the current rendered UI captured.
  • review-gated: user invokes reviewers or says the result must pass review.
  • component-lab: user asks to build, expand, or audit UI Lab/component inventory; route out to the lifecycle/component-lab workflow first.

In advice-only, produce the smallest useful UI direction and stop. In explain-only, trace the rendered reason from screenshot to component/CSS/data source and stop with the likely fix direction, not a patch. In implement, make the code change. If the user gives screenshots plus vague language, infer the concrete pain from the image and surrounding product state.

In component-lab, do not start a narrow polish pass. The owning workflow must first define component coverage, context-required labeling, route behavior, tests, and browser proof. Return to this skill only for a concrete visual fix inside an already-scoped component-lab task.

2. Build a small evidence packet

Gather only the context needed for this UI surface:

  • current route, component, and API client involved
  • relevant nearby tests
  • doc/engineering/DESIGN.md for visible UI defaults when the change is layout-sensitive
  • existing components, tokens, icons, and status labels before inventing new UI
  • screenshot or browser state when the user provided or requested visual proof

Check git status --short --branch before editing. Preserve unrelated dirty worktree changes.

3. Make the smallest coherent UI change

Prefer local product consistency over a generic design pattern:

  • reuse existing Rudder components and status vocabulary
  • keep operational screens compact, scannable, and calm
  • remove redundant copy instead of explaining the UI inside the UI
  • avoid wrapping cards inside cards
  • avoid decorative treatment that competes with work content
  • keep controls discoverable but not oversized
  • preserve keyboard, selection, copy, and accessibility behavior when editing input or composer surfaces

When adding visible state such as issue status, use real existing data from the surface's context snapshot or API response. Do not hard-code status text just to make the UI look right.

4. Keep contracts aligned

If the UI change needs data that is not already present, trace the contract:

  • shared type or validator
  • server route or service response
  • UI API client and component props
  • tests and E2E expectations

Do not silently introduce an organization-scoping, permission, or persistence change while doing a visual polish task. If that is needed, call it out and scope it as feature work.

5. Validate behavior and visual result

Run the narrowest meaningful automated checks first:

  • component or page test for the touched surface
  • E2E test when the user-visible workflow changed
  • typecheck/build when shared contracts changed

For visible UI changes, verify the rendered result with a browser, Desktop shell, screenshot, or equivalent visual inspection. Prefer the available browser automation path for local routes. If browser verification is blocked, state the exact blocker and do not describe the layout as visually proven.

When the defect is alignment, line height, avatar/text/time centering, column width, or row rhythm, a screenshot alone is often too weak. Use realistic data for the actual object being aligned, such as a real agent avatar instead of a placeholder icon, a long activity label, and the timestamp or action controls that appear in production. Then add at least one measurable proof when practical:

  • DOM bounding boxes for the avatar, primary text, secondary text, timestamp, and row container
  • centerline or top/bottom delta showing the items share the intended row axis
  • screenshot with the real fixture state, saved outside the repo

If Browser or the test harness cannot collect geometry, say that the alignment proof is visual-only. Do not claim a row-alignment fix is fully proven from a unit test that renders placeholder data instead of the production-shaped row.

For follow-up corrections from the user, such as "这颜色不对", "没修好", or "这里还是不对", inspect the rendered state again before editing further. Treat the user's screenshot as evidence that the previous proof was incomplete, not as a reason to keep patching blindly.

Store temporary screenshots outside the repo, for example under /tmp.

6. Commit only this task

After validation, stage only files changed for this task. Do not include unrelated dirty worktree changes. Use a Conventional Commit message such as:

  • fix: align automation settings rows
  • feat: show issue status in messenger cards
  • chore: remove redundant organizations settings page

Push the current branch when the repository rules and current branch state allow it.

Output Expectations

For implementation tasks, hand off with:

  • what changed, in product terms
  • key files touched
  • validation run and any blocked checks
  • screenshot path or rendered proof when the change is visual
  • commit hash and push status when committed

For advice-only tasks, hand off with:

  • the product diagnosis
  • the recommended UI direction
  • any explicit non-goals
  • the implementation shape if the user approves edits

Common Failure Modes

  • Over-solving a small screenshot complaint with a broad redesign.
  • Routing every small screenshot complaint through a full advisor/reviewer loop when a lightweight UI-polish pass is enough.
  • Treating a visual issue as pure CSS when the real problem is wrong data, wrong route, or redundant object modeling.
  • Claiming visual verification after browser automation timed out.
  • Claiming an alignment fix from placeholder fixtures when the real surface uses agent avatars, long labels, timestamps, badges, or row actions.
  • Shipping a nice-looking state badge that reads stale or mock data.
  • Mixing unrelated dirty files into the commit.
  • Using advisor-review-loop-maintainer for every small UI tweak, slowing down work that only needed a focused polish pass.
  • Treating UI Lab or component-inventory work as a small cosmetic issue and stopping after screenshots or style tweaks without coverage and fixture proof.

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 Rudder Ui Polish Maintainer AI skill do?

Use when implementing screenshot-driven or narrow Rudder UI polish: density, alignment, spacing, labels, cards, menus, hover states, empty states, onboarding steps, redundant pages, compact workflows, screenshots, or small visible interaction fixes.

Why use Rudder Ui Polish Maintainer on TypingMind?

Because you install it once and use it with any model. Rudder Ui Polish Maintainer 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 Rudder Ui Polish Maintainer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Undertone0809/rudder/tree/main/agent-skills-bak/maintainer/rudder-ui-polish-maintainer. 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 Rudder Ui Polish Maintainer?

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 Rudder Ui Polish Maintainer?

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

Is the Rudder Ui Polish Maintainer AI skill free?

Yes. It is published on GitHub by Undertone0809 under the Apache-2.0 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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