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Form Follows Function Success Criteria

Community
Deibler
form-follows-function-success-criteria

Use this skill when the team is in a form-vs-function debate and needs to step back to define what "success" actually means for the design. Trigger when stakeholders disagree about visual treatment, when a design feels off and no one can articulate why, or when reviewing a design against an unclear brief. Sub-aspect of `form-follows-function`; read that first.

Overview

PublisherDeibler
Repositoryuniversal-design-principles
Skill nameform-follows-function-success-criteria
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 Form Follows Function Success Criteria 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/aesthetics-and-emotion-principles/skills/form-follows-function-success-criteria
  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/aesthetics-and-emotion-principles/skills/form-follows-function-success-criteria .claude/skills/form-follows-function-success-criteria
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Form Follows Function Success Criteria 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 Form Follows Function Success Criteria 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 Form Follows Function Success Criteria 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.

Defining success criteria explicitly

The book's reframe of form-follows-function: instead of asking "what should be omitted?", ask "what's critical to this design's success?". Then weigh form and function against those criteria. The discipline is making success criteria explicit rather than assuming.

Common implicit success criteria

Without explicit criteria, teams default to assumed criteria — often without alignment:

  • Designer assumes: visual elegance.
  • Engineer assumes: implementation simplicity.
  • Product manager assumes: feature completeness.
  • Marketing assumes: brand differentiation.
  • Stakeholder assumes: stakeholder approval.

When the assumed criteria differ, every design decision becomes contentious. Explicit criteria make decisions defensible.

Naming success criteria

For a given design, candidates include:

  • User performance (speed, accuracy, error rate).
  • User satisfaction / preference.
  • Business outcomes (conversion, retention, revenue).
  • Brand differentiation (does this look unmistakably like us?).
  • Accessibility / inclusion.
  • Implementation simplicity / cost.
  • Long-term maintainability.
  • Aesthetic / emotional response.

Most designs serve multiple criteria; the question is which dominate when they conflict.

A team exercise

For a design in dispute:

  1. List the criteria the design should serve.
  2. Rank them by priority for this specific surface.
  3. For each candidate design choice, evaluate against the top 2–3 criteria.
  4. Pick the choice that does best on top criteria; accept trade-offs on lower ones.

This conversation surfaces hidden disagreements about what the design is for. Resolving those usually resolves the surface debates.

Worked example

A landing-page hero section is in dispute. Designer wants minimalist (one headline, one CTA); marketing wants rich (headline, deck, three feature bullets, social proof, primary + secondary CTA).

Without explicit criteria, the debate is irresolvable. Each side has a defensible position.

With explicit criteria:

  • Conversion rate: rich variants tend to convert better in A/B tests for new visitors. Marketing's position favored.
  • Brand differentiation: minimalist often differentiates better in cluttered spaces. Designer's position favored.
  • Mobile experience: minimalist tends to perform better on small screens. Designer's position favored.

If conversion rate is the dominant criterion, marketing wins this round; ship rich and A/B test. If brand differentiation is dominant, designer wins. The criteria choice resolves the debate.

When form genuinely competes with function

Some legitimate trade-offs:

  • Visual polish vs. load time — animations, large images cost performance.
  • Brand differentiation vs. convention adherence — distinctive design departs from familiar patterns.
  • Aesthetic minimalism vs. discoverability — fewer visible elements = harder to find features.
  • Custom vs. native components — custom looks distinctive but is more expensive and risks accessibility.

Each trade-off should be made deliberately, with success criteria informing the choice.

Anti-patterns

  • Implicit criteria. Each team member assumes different criteria; debates are unresolvable.
  • All-criteria-must-be-served. Trying to optimize for everything produces designs that serve nothing well.
  • Designer-as-arbiter. "I'm the designer, so I get to decide" — without explicit criteria, this is unconvincing.
  • Stakeholder-as-arbiter. "The CEO likes it" — same problem.

Heuristics

  1. The criteria-naming exercise. Before designing, list and rank success criteria. Get team alignment.
  2. The trade-off-explicitness check. When trading off, name what's being sacrificed. "We're sacrificing brand differentiation for convention adherence."
  3. The dominant-criterion test. When stuck, ask: which criterion matters most for this surface (not in general)? That answer often resolves.

Related sub-skills

  • form-follows-function (parent).
  • form-follows-function-as-axiom — the descriptive interpretation.
  • hierarchy-of-needs (interaction) — Maslow-derived ordering of design needs.
  • flexibility-usability-tradeoff — explicit trade-off framing.

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 Form Follows Function Success Criteria AI skill do?

Use this skill when the team is in a form-vs-function debate and needs to step back to define what "success" actually means for the design. Trigger when stakeholders disagree about visual treatment, when a design feels off and no one can articulate why, or when reviewing a design against an unclear brief. Sub-aspect of `form-follows-function`; read that first.

Why use Form Follows Function Success Criteria on TypingMind?

Because you install it once and use it with any model. Form Follows Function Success Criteria 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 Form Follows Function Success Criteria in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Deibler/universal-design-principles/tree/main/plugins/aesthetics-and-emotion-principles/skills/form-follows-function-success-criteria. 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 Form Follows Function Success Criteria?

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 Form Follows Function Success Criteria?

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

Is the Form Follows Function Success Criteria 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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