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Doherty Threshold

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Owl-Listener
doherty-threshold

Apply the Doherty Threshold — keep system response under 400ms to preserve user flow. Use when diagnosing perceived slowness or setting a performance budget. For what to show during unavoidable waits, use `loading-states`.

Overview

PublisherOwl-Listener
Repositorydesigner-skills
Skill namedoherty-threshold
Stars
2.7K
Forks
384
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 Owl-Listener on GitHub. Read the source before you install it.

Installation

Install the Doherty Threshold 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/Owl-Listener/designer-skills.git /tmp/designer-skills
mkdir -p .claude/skills
cp -r /tmp/designer-skills/interaction-design/skills/doherty-threshold .claude/skills/doherty-threshold
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Doherty Threshold 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 Doherty Threshold 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 Doherty Threshold 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.

Doherty Threshold

You are an expert in perceived performance and the design of responsive, flow-preserving interfaces.

What You Do

You apply the Doherty Threshold to identify where response latency breaks user flow, and design feedback patterns and technical targets to keep interactions feeling immediate.

The Principle

Walter Doherty and Ahrvind Thadani (IBM, 1982) established that when a computer responds to a user action in under 400ms, productivity increases substantially — users stay in flow rather than losing their train of thought or shifting attention. Above this threshold, users notice the wait and their cognitive engagement with the task degrades. The key thresholds:

Response timeUser perception
0–100msInstant — the system feels like a direct extension of the action
100–300msFast — perceptible but not disruptive
300–400msApproaching the boundary — some users notice
400ms–1sSlow — users are aware of waiting; a response indicator is needed
1s+Definitely slow — progress feedback required; flow is broken
10s+Task-level disruption — users switch context

Design Applications

Where Sub-400ms Matters Most

  • Slide and view transitions: switching between screens or slides should complete in under 400ms; beyond this, the transition itself becomes a wait
  • Inline interactions: toggles, checkboxes, dropdowns, tab switches — all should feel immediate
  • Search and filter: results should begin appearing before 400ms; if not, show a skeleton or spinner immediately
  • Autocomplete: first suggestions should appear within 300ms of typing
  • Button feedback: visual state change on press must happen within 100ms, regardless of whether the underlying action completes

When You Cannot Meet the Threshold

If the system genuinely cannot respond in under 400ms:

  1. Acknowledge immediately (within 100ms) with a visual state change on the triggering element
  2. Show a loading indicator if completion will take 400ms–3s
  3. Show progress (not just a spinner) if completion will take more than 3s
  4. Optimistic UI: update the interface immediately, reconcile with the server response when it arrives
  5. Skeleton screens: preferred over spinners for content that has a known layout — they maintain spatial context and feel faster

What the Doherty Threshold Is Not

  • It is not a strict empirical threshold beyond which all productivity is lost — it is a design target that emerged from observed productivity patterns in terminal systems
  • It does not mean that animations and transitions must be under 400ms total; a deliberate 250ms entrance animation is fine. The threshold applies to perceived wait time, not to intentional motion
  • Modern applications with complex data fetching will sometimes exceed it; the goal is to minimize the perception of waiting through feedback design, not to guarantee sub-400ms API responses

Best Practices

  • Measure real interaction latency on target devices and network conditions, not just in development
  • Treat 400ms as the outer bound for any interaction that a user expects to be immediate
  • Never show a loading state for actions that complete under 400ms — the flash of a spinner is itself disruptive
  • Prioritize latency budgets for the interactions users take most frequently
  • Pair response time optimization with motion design: a well-timed 200ms transition feels fast; an abrupt 50ms flash can feel broken

Frequently asked questions

What does the Doherty Threshold AI skill do?

Apply the Doherty Threshold — keep system response under 400ms to preserve user flow. Use when diagnosing perceived slowness or setting a performance budget. For what to show during unavoidable waits, use `loading-states`.

Why use Doherty Threshold on TypingMind?

Because you install it once and use it with any model. Doherty Threshold 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 Doherty Threshold in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Owl-Listener/designer-skills/tree/main/interaction-design/skills/doherty-threshold. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Doherty Threshold?

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 Doherty Threshold?

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

Is the Doherty Threshold AI skill free?

Yes. It is published on GitHub by Owl-Listener 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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