Ux Loaders And Progress logo

Ux Loaders And Progress

Organization
Uxcel-Lab
ux-loaders-and-progress

Design or critique loading states and progress indicators — match the feedback type (spinner, text, determinate bar, skeleton, progress tracker) to the wait duration and task structure, and manage perceived performance. Trigger when the user asks to design or review loaders, spinners, loading states, skeleton screens, progress bars, progress trackers, steppers, or multi-step flow progress.

Overview

PublisherUxcel-Lab
Repositoryproduct-skills
Skill nameux-loaders-and-progress
Stars
35
Forks
8
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 Uxcel-Lab on GitHub. Read the source before you install it.

Installation

Install the Ux Loaders And Progress 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/Uxcel-Lab/product-skills/tree/main/ux/components/loaders-and-progress
  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/Uxcel-Lab/product-skills.git /tmp/product-skills
mkdir -p .claude/skills
cp -r /tmp/product-skills/ux/components/loaders-and-progress .claude/skills/ux-loaders-and-progress
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ux Loaders And Progress 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 Ux Loaders And Progress 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 Ux Loaders And Progress 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.

Loaders & Progress Skill

How this skill behaves (read first)

This is a generative skill. The default failure modes: one spinner for everything (a full-page spinner whether the wait is 1 second or 60), no endpoint when one exists (indeterminate loops for measurable tasks), and progress theater (trackers on 2-step forms, percentages that lie). The feedback type is determined by wait duration and task structure — and a loader's real job is shaping perceived time, not decorating it. This skill gates:

  1. Establish the wait type — how long, is it measurable, what initiated it, is it a multi-step journey?
  2. Apply the always-true core — the duration ladder, placement, state visibility.
  3. Surface the context-dependent decisions (skeletons, custom animation, tracker labeling, save/autosave) with trade-offs.

Then it hands off to ux-heuristics-audit, ux-accessibility-audit, ux-aesthetics-audit, and ux-microcopy-audit for validation.


Step 0 — Establish the wait type

Four questions pick the indicator:

  • How long is the wait? <1s → often no indicator needed; 1–5s → indeterminate (spinner/text); ~10s+ → determinate with a visible endpoint; long/variable content loads → skeleton.
  • Is progress measurable? If the system can know completion % (upload, export), users get a determinate indicator — an endless spinner on a measurable task reads as "maybe broken."
  • What triggered it? A user click (button) → inline feedback at the action; content loading → skeleton in the content's place; a background process → unobtrusive.
  • Is it a multi-step user journey (form, checkout, onboarding) rather than a system wait? → progress tracker, not loader — different component, different rules (below).

The always-apply core (correct for almost every case)

The duration ladder (loaders)

  • 1–5s: indeterminate — spinner, or a text loader ("Saving…") with a subtle animation (pulsing dots). Never let a looped animation run past ~5s — looping with no endpoint is where frustration starts.
  • 10s+: determinate — progress bar or filling circle with a clear endpoint; add a percentage label for precision on long tasks.
  • Content loads: skeleton screens — placeholders mimicking the coming layout (text blocks, image areas), filled sequentially top-to-bottom. They beat spinners on perceived speed because they promise structure.
  • No full-page spinners. They give zero sense of progress and suggest malfunction. Spinners live small and inline: in a button after click, in a table row, beside the thing that's loading.

Placement = meaning

  • Near the action that started it (inline with the submit button), on the content that's loading (overlay/skeleton), or centered only when the entire page is genuinely loading.
  • In-button progress: the button shows a spinner and becomes unclickable — feedback and double-submit prevention in one move.

Progress trackers (multi-step journeys)

  • Three states, always visible: completed (checkmark/green), current (visually distinct — the "you are here" pin), remaining (muted, activating on arrival).
  • Label the steps — titles restore context for users who got distracted and make the journey scannable.
  • 5–7 steps maximum. A tracker doesn't shorten a form; if steps multiply, the flow needs restructuring, not a longer tracker.
  • A tracker is feedback, not decoration: it serves visibility of system status — users should always know what they did, where they are, and what's left.

The context-dependent decisions (surface, don't auto-apply)

DecisionApply whenAvoid / adapt whenDefault recommendation
Skeleton vs. spinner for contentLayout-known content (feeds, cards, tables) — skeletons cut perceived waitTiny, instant loads (skeleton flash looks broken)Skeleton for content areas; inline spinner for actions
Progress tracker at all≥3 logical stages (checkout, surveys, registration)Short forms — a tracker on 2 steps adds ceremonyNumbered/labeled steps from 3 stages up
Tracker labeling: titles vs. numbers vs. %Titles for scannability; numbers/% for motivation on long journeysPercentages that jump erratically (trust killer)Titles + step count; % only when it maps honestly to effort
Bar vs. numbered stepsBar for short journeys (overall progress feel); steps for ≥3 distinct milestonesBars pretending precision they don't haveSteps for forms; bar for processing
Carousel trackers (dots)Onboarding/walkthroughs with few skippable screensDirectional, non-skippable flowsDots for walkthroughs only
Vertical trackersStatus timelines (delivery tracking, application stages)Standard form navigationVertical for event/status histories
Save / autosave progressAny journey over a couple of minutesRelying on the tracker alone to retain usersAutosave + return-to-last-step for long flows
Custom branded loadersBrand moments where the wait is unavoidable; determinate/indeterminate decided firstNovelty that obscures progressFunction first, personality second

Validate the result (orchestration)

Hand-offs name each lens by its installable skill name. Invoke one only if that skill is installed; if it isn't, this skill's own core already carries these rules — proceed without it rather than blocking.

After generating or revising, hand the result to the audit lenses rather than declaring it done. These are candidate lenses — posture is set by docs/orchestration-policy.md, or route the whole thing through ux-design-review. Here, heuristics and microcopy are Tier A (auto-run); accessibility, aesthetics, and mobile-responsiveness are Tier B (offered) — under an existing design system aesthetics is suppressed and accessibility narrows to usage; mobile-responsiveness applies only on mobile. If the user invoked this skill for one specific thing, respect that scope.

  • ux-heuristics-audit (Tier A) — visibility of system status is this component's entire reason to exist; also error prevention (disabled buttons during processing).
  • ux-accessibility-audit (Tier B — offer; narrow under a design system) — loading states announced to screen readers, animation respecting reduced-motion preferences, contrast of muted tracker steps.
  • ux-aesthetics-audit (Tier B — offer; suppress under a design system) — skeleton fidelity to real layout, animation restraint, tracker visual hierarchy.
  • ux-microcopy-audit (Tier A) — text-loader wording, step labels, percentage/status phrasing.
  • ux-mobile-responsiveness-audit (Tier B — offer; applies only on mobile) — when the context is mobile: tracker compression, skeleton reflow.

If the audits surface a conflict (e.g., brand animation vs. perceived speed), resolve back toward the primary task: the user is waiting — every design choice either shortens that wait perceptually or lengthens it.


Common do/don't patterns

❌ Don't✅ Do
Full-page spinner for everythingInline spinners, skeletons for content, centered only for true page loads
Looping spinner on a 60-second uploadDeterminate bar with endpoint + percentage
Spinner where the layout is knownSkeleton screens, filled sequentially
Clickable button while its action processesIn-button spinner, button disabled
Loader floating far from its causeFeedback at the action or on the content
Progress tracker on a 2-step formTrackers from 3 stages; short forms stay plain
Unlabeled tracker dotsStep titles + clear completed/current/remaining states
11-step tracker as a fix for a bloated form5–7 steps max; restructure the flow
% that jumps 10→80→82→…Honest progress mapping, or use steps
Long form with no saveAutosave + return to the last step
Ship without checkingHand off to heuristics + accessibility + aesthetics + microcopy

Source lessons (Uxcel)

Frequently asked questions

What does the Ux Loaders And Progress AI skill do?

Design or critique loading states and progress indicators — match the feedback type (spinner, text, determinate bar, skeleton, progress tracker) to the wait duration and task structure, and manage perceived performance. Trigger when the user asks to design or review loaders, spinners, loading states, skeleton screens, progress bars, progress trackers, steppers, or multi-step flow progress.

Why use Ux Loaders And Progress on TypingMind?

Because you install it once and use it with any model. Ux Loaders And Progress 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 Ux Loaders And Progress in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Uxcel-Lab/product-skills/tree/main/ux/components/loaders-and-progress. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ux Loaders And Progress?

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 Ux Loaders And Progress?

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

Is the Ux Loaders And Progress AI skill free?

Yes. It is published on GitHub by Uxcel-Lab 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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