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Feedback Loop States And Latency

Community
Deibler
feedback-loop-states-and-latency

Use this skill when designing the visible states an interactive element passes through (idle / pending / success / error) and matching feedback timing to the user's perceptual thresholds. Trigger when designing button states, form-submit flows, file-upload progress, loading screens, or any interaction whose response time is variable. Sub-aspect of `feedback-loop`; read that first.

Overview

PublisherDeibler
Repositoryuniversal-design-principles
Skill namefeedback-loop-states-and-latency
Stars
9
Forks
3
Bundled files
1
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 Deibler on GitHub. Read the source before you install it.

Installation

Install the Feedback Loop States And Latency 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/Deibler/universal-design-principles/tree/main/plugins/interaction-and-control-principles/skills/feedback-loop-states-and-latency
  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/Deibler/universal-design-principles.git /tmp/universal-design-principles
mkdir -p .claude/skills
cp -r /tmp/universal-design-principles/plugins/interaction-and-control-principles/skills/feedback-loop-states-and-latency .claude/skills/feedback-loop-states-and-latency
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Feedback Loop States And Latency 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 Feedback Loop States And Latency 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 Feedback Loop States And Latency 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.

Feedback states and latency thresholds

Most interactive actions pass through a small set of visible states; the system must communicate each. The latency of each state determines what feedback is appropriate — a 50ms response needs no spinner, a 5s response needs progress info, a 50s response needs estimated time remaining.

The four states

Idle

The element is interactive and waiting. Affordance signals "you can do this." Static styling.

Pending

Action triggered; system working. Disable trigger to prevent re-submit; show indicator if wait > ~500ms.

Success

Action succeeded. Show the result in-place where possible; toast/banner if the result is on another surface.

Error

Action failed. In-context, specific, actionable error message.

html
<button id="action" data-state="idle">
  <span class="label">Save</span>
  <span class="spinner" hidden></span>
</button>

<style>
  button[data-state="pending"] { cursor: wait; opacity: 0.7; }
  button[data-state="pending"] .spinner { display: inline-block; }
  button[data-state="success"] { background: var(--success); }
  button[data-state="error"] { background: var(--destructive); }
</style>

Latency thresholds (Miller, Card et al., Doherty)

LatencyThresholdPattern
< 100ms"Instant"No indicator. Just respond.
100–400ms"Responsive"Light state change (button briefly disabled).
400ms–1s"Noticeable"Spinner or progress micro-animation.
1–10s"Waiting"Spinner with status text.
> 10s"Long"Progress bar with estimated time remaining; cancel option.

Doherty Threshold (~400ms): response times under this keep users in flow. Above this, attention drifts and engagement drops.

Optimistic UI

For actions where the success rate is high and the action is reversible, update the UI as if the action succeeded immediately, then commit in the background. If the action fails, roll back visibly with an error message.

js
async function toggleStar(item) {
  // Optimistic
  item.starred = !item.starred;
  render();

  try {
    await api.updateStar(item.id, item.starred);
  } catch (err) {
    // Rollback with feedback
    item.starred = !item.starred;
    render();
    showToast(`Couldn't update: ${err.message}`);
  }
}

The user gets instant feedback; failure is the exception, handled with explicit feedback.

Skeleton screens vs. spinners

For loading content (not actions), prefer skeleton screens to spinners:

html
<!-- While data loads -->
<article class="post-skeleton">
  <div class="title-skel"></div>
  <div class="meta-skel"></div>
  <div class="body-skel"></div>
  <div class="body-skel"></div>
</article>

Skeletons:

  • Show the page's structure immediately.
  • Reduce perceived load time.
  • Reduce visual disruption when real content arrives.

Spinners are better when the wait isn't structural (a single action's pending state) or when the location of the result isn't predictable.

Progress indicators for long operations

For operations > 10s:

  • Determinate progress bar (when % complete is known) with status text.
  • Time-remaining estimate (after enough data to estimate accurately).
  • Cancel option (don't trap the user in a stuck operation).
  • Background continuation option for very long ops (let them work elsewhere).
html
<div class="upload">
  <p>Uploading <strong>file.zip</strong></p>
  <progress max="100" value="42">42%</progress>
  <p class="status">42% — about 2 minutes remaining</p>
  <button>Cancel</button>
</div>

Error feedback: in-context

Errors should appear with the element that caused them, not in a generic page banner.

html
<div class="field" data-state="error">
  <label for="email">Email</label>
  <input id="email" type="email" aria-invalid="true" aria-describedby="email-error" />
  <p id="email-error" class="error">
    We couldn't find an account with this email.
    <a href="/signup">Sign up?</a>
  </p>
</div>

aria-invalid and aria-describedby make the error programmatically associated; screen readers announce both together.

Anti-patterns

  • Silent commits. Button submits with no visible response.
  • Blink-and-miss success. Confirmation appears for 100ms.
  • Generic errors. "Something went wrong" with no specific or actionable info.
  • Spam confirmations. Every save shows a "Saved!" toast users dismiss on autopilot.
  • Wrong state colors. Pending state same color as success.
  • Spinners over content the user is reading. Distracting; use skeleton or peripheral indicator.

Heuristics

  1. The "what state am I in?" check. At any moment during an action, can the user tell which of the four states they're in? If not, feedback is missing.
  2. The latency-stopwatch. Time each major action. Match feedback to the threshold the action falls into.
  3. The error-recovery audit. For each error feedback, can the user tell what to do next? If "no idea," rewrite the message.

Related sub-skills

  • feedback-loop (parent).
  • feedback-loop-positive-vs-negative — loop architecture; this skill is loop implementation.
  • accessibility-operable — aria-live regions communicate states to screen readers.
  • forgiveness — error feedback is recovery's first step.

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 Feedback Loop States And Latency AI skill do?

Use this skill when designing the visible states an interactive element passes through (idle / pending / success / error) and matching feedback timing to the user's perceptual thresholds. Trigger when designing button states, form-submit flows, file-upload progress, loading screens, or any interaction whose response time is variable. Sub-aspect of `feedback-loop`; read that first.

Why use Feedback Loop States And Latency on TypingMind?

Because you install it once and use it with any model. Feedback Loop States And Latency 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 Feedback Loop States And Latency in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Deibler/universal-design-principles/tree/main/plugins/interaction-and-control-principles/skills/feedback-loop-states-and-latency. 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 Feedback Loop States And Latency?

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 Feedback Loop States And Latency?

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

Is the Feedback Loop States And Latency AI skill free?

It is published on GitHub by Deibler. 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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