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Feedback Indicators

Community
dylantarre
feedback-indicators

Use when confirming user actions - success checkmarks, error alerts, form validation, save confirmations, or any animation acknowledging what the user did.

Overview

Publisherdylantarre
Repositoryanimation-principles
Skill namefeedback-indicators
Stars
84
Forks
12
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 dylantarre on GitHub. Read the source before you install it.

Installation

Install the Feedback Indicators 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/dylantarre/animation-principles.git /tmp/animation-principles
mkdir -p .claude/skills
cp -r /tmp/animation-principles/skills/05-by-animation-type/feedback-indicators .claude/skills/feedback-indicators
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Feedback Indicators 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 Indicators 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 Indicators 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 Indicator Animations

Apply Disney's 12 principles to action confirmation animations.

Principle Application

Squash & Stretch: Success checkmarks can scale with overshoot. Compress on draw, expand on complete.

Anticipation: Brief gather before feedback appears. 50ms of preparation before the confirmation.

Staging: Feedback appears at the action location. Button shows checkmark, field shows validation.

Straight Ahead vs Pose-to-Pose: Define feedback states: neutral → processing → success/error.

Follow Through & Overlapping: Icon animates, then label appears. Stagger confirmation elements.

Slow In/Slow Out: Success: ease-out (confident arrival). Error: ease-in-out (shake settles).

Arcs: Checkmarks draw in arcs, not straight lines. Error X's cross naturally.

Secondary Action: Checkmark draws + color shifts + scale bounces for rich feedback.

Timing:

  • Instant feedback: 100-200ms (form validation)
  • Success confirmation: 300-500ms (checkmark draw)
  • Error indication: 400ms (shake + message)
  • Auto-dismiss: 2000-4000ms after appearance

Exaggeration: Success deserves celebration. Overshoot scale to 1.2, bold colors, confident motion.

Solid Drawing: Feedback icons must be clear at a glance. Recognition in 100ms or less.

Appeal: Positive feedback should feel rewarding. Negative feedback firm but not punishing.

Timing Recommendations

Feedback TypeDurationAuto-dismissEasing
Inline Validation150msNoease-out
Checkmark Draw400ms3000msease-out
Success Toast300ms4000msease-out
Error Shake400msNoease-in-out
Error Toast300ms6000msease-out
Save Indicator200ms2000msease-out

Implementation Patterns

css
/* Checkmark draw */
.checkmark {
  stroke-dasharray: 50;
  stroke-dashoffset: 50;
  animation: draw-check 400ms ease-out forwards;
}

@keyframes draw-check {
  to { stroke-dashoffset: 0; }
}

/* Success with scale */
.success-icon {
  animation: success 500ms cubic-bezier(0.34, 1.56, 0.64, 1) forwards;
}

@keyframes success {
  0% { transform: scale(0); opacity: 0; }
  60% { transform: scale(1.2); opacity: 1; }
  100% { transform: scale(1); opacity: 1; }
}

/* Error shake */
.error-shake {
  animation: shake 400ms ease-in-out;
}

@keyframes shake {
  0%, 100% { transform: translateX(0); }
  20%, 60% { transform: translateX(-6px); }
  40%, 80% { transform: translateX(6px); }
}

/* Inline validation */
.field-valid {
  animation: valid-pop 200ms ease-out;
}

@keyframes valid-pop {
  0% { transform: scale(0.8); opacity: 0; }
  100% { transform: scale(1); opacity: 1; }
}

SVG Checkmark Pattern

html
<svg class="checkmark" viewBox="0 0 24 24">
  <circle cx="12" cy="12" r="10" fill="#10B981"/>
  <path
    class="check-path"
    d="M7 13l3 3 7-7"
    stroke="white"
    stroke-width="2"
    fill="none"
  />
</svg>

Auto-Dismiss Pattern

javascript
// Show success, auto-hide
element.classList.add('success-visible');

setTimeout(() => {
  element.classList.remove('success-visible');
  element.classList.add('success-hidden');
}, 3000);

Key Rules

  1. Feedback must appear within 100ms of action
  2. Success states: celebrate briefly, don't linger
  3. Error states: persist until user acknowledges
  4. Always provide text alongside icons for accessibility
  5. prefers-reduced-motion: instant state, no animation

Frequently asked questions

What does the Feedback Indicators AI skill do?

Use when confirming user actions - success checkmarks, error alerts, form validation, save confirmations, or any animation acknowledging what the user did.

Why use Feedback Indicators on TypingMind?

Because you install it once and use it with any model. Feedback Indicators 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 Indicators in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dylantarre/animation-principles/tree/main/skills/05-by-animation-type/feedback-indicators. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Feedback Indicators?

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 Indicators?

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

Is the Feedback Indicators AI skill free?

Yes. It is published on GitHub by dylantarre 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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