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Game Design Zeigarnik Effect Audit

Community
Stanestane
game-design-zeigarnik-effect-audit

Audit a game, feature, task system, quest flow, event track, puzzle chain, progression layer, or return loop through the lens of the Zeigarnik effect: the tension created by incomplete, interrupted, or unresolved tasks. Use when evaluating whether a design creates healthy return motivation through open loops, whether it leaves players with productive unfinished business, or whether it turns incompletion into anxiety, clutter, guilt, or manipulative pressure.

Overview

PublisherStanestane
Repositorygame-design-skills-bundle
Skill namegame-design-zeigarnik-effect-audit
Stars
87
Forks
18
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Stanestane on GitHub. Read the source before you install it.

Installation

Install the Game Design Zeigarnik Effect Audit 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/Stanestane/game-design-skills-bundle/tree/master/game-design-zeigarnik-effect-audit
  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/Stanestane/game-design-skills-bundle.git /tmp/game-design-skills-bundle
mkdir -p .claude/skills
cp -r /tmp/game-design-skills-bundle/game-design-zeigarnik-effect-audit .claude/skills/game-design-zeigarnik-effect-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Game Design Zeigarnik Effect Audit 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 Game Design Zeigarnik Effect Audit 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 Game Design Zeigarnik Effect Audit 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.

Game Design Zeigarnik Effect Audit

Audit a design by asking how it uses unfinished business and whether that unfinishedness creates useful tension or just psychic clutter.

Use this skill when a feature depends on incomplete tasks, suspended goals, unresolved quests, unfinished collections, interrupted runs, dangling mysteries, near-complete progress bars, or other forms of cognitive open-loop tension. The goal is to evaluate whether the design creates healthy return pull, curiosity, and momentum, or whether it produces guilt, overwhelm, clutter, and coercive pressure.

Read references/family-conventions.md when you want the shared style, prioritization, and diagnosis rules for this game-design skill family. Read references/output-patterns.md when you want the preferred recommendation and minimal-fix structure.

Core principle

Unfinished things stick in the mind.

In games, that can be powerful. An incomplete task can create:

  • return motivation
  • curiosity
  • anticipation
  • desire for closure
  • mental continuity between sessions

But open loops become toxic when they create:

  • obligation without excitement
  • clutter without priority
  • anxiety without clarity
  • guilt without meaningful choice
  • manipulative pressure to return

The point is not merely to leave things unfinished. The point is to leave the right things unfinished in the right way.

What to produce

Generate:

  1. Open-loop profile - what unresolved elements the design leaves active in the player's mind
  2. Return-tension diagnosis - whether incompletion creates healthy pull or unhealthy pressure
  3. Clarity and prioritization diagnosis - whether the player knows what is unfinished and why it matters
  4. Clutter and coercion risks - where open loops become noise, guilt, or manipulative burden
  5. Design actions - what to sharpen, resolve, stage, reduce, or frame differently

Process

1. Define the audit target

Clarify:

  • what exact system, flow, or experience slice is being audited
  • what unresolved elements matter most
  • whether the concern is retention, curiosity, task load, or psychological pressure

Write:

  • Audit target
  • Open-loop type
  • Primary concern

2. Identify the unresolved loops

Look for things like:

  • incomplete quests
  • partial event tracks
  • nearly finished collections
  • dangling narrative mysteries
  • interrupted crafting or building goals
  • unresolved social obligations
  • suspended runs or puzzle attempts
  • pending claim states
  • visible near-misses

Ask:

  • what remains unfinished?
  • what keeps that unfinishedness mentally active?
  • is the loop explicit, implied, or ambient?

3. Classify the kind of tension being created

Useful categories include:

  • curiosity tension
  • completion tension
  • competence tension
  • social obligation tension
  • reward anticipation tension
  • scarcity/FOMO tension
  • guilt/maintenance tension

Not all tension is equally healthy.

4. Audit clarity and closure path

Ask:

  • does the player understand what is unresolved?
  • do they know how to resume or resolve it?
  • is the next step obvious enough to act on?
  • is there one clean open loop or a pile of competing ones?
  • does the system preserve meaningful stopping points, or does it always leave the player hanging messily?

5. Diagnose healthy versus unhealthy open loops

Healthy open loops tend to be:

  • legible
  • meaningful
  • self-directed
  • motivating
  • finite enough to imagine closure

Unhealthy open loops tend to be:

  • noisy
  • coercive
  • low-value
  • ambiguous
  • too numerous
  • attached to shame or maintenance burden

Ask:

  • does the player return because they want closure, or because they feel nagged?
  • is the unfinishedness energizing or depleting?
  • is the pressure chosen or imposed?

6. Check interaction with session structure

Ask:

  • does the system give players safe stopping points?
  • does it create a clear "one more thing" pull?
  • does it overload session endings with too many unresolved hooks?
  • does it preserve continuity between sessions without creating dread?

This is especially important for retention design and return loops.

7. Diagnose Zeigarnik failure patterns

Look for:

  • too many simultaneous unfinished tasks
  • near-completion bait with weak actual payoff
  • open loops that matter only because the UI keeps nagging about them
  • unresolved states with poor re-entry clarity
  • social obligations that convert return into guilt
  • cliffhangers without enough meaning to justify the tension
  • retention loops that feel manipulative rather than naturally compelling

8. Check audience sensitivity

Ask whether:

  • completionists are energized while casual players are overwhelmed
  • new players feel buried under unresolved systems
  • lapsed players return to a wall of unfinished business and bounce
  • high-engagement players enjoy layered open loops that would suffocate lighter audiences

9. Convert findings into design changes

For each issue, specify:

  • Open-loop problem
  • Why it creates the wrong kind of tension
  • Suggested change
  • Expected effect on return motivation or psychological load

Examples:

  • reduce simultaneous unfinished objectives -> lowers clutter and increases focus
  • improve resume clarity -> turns vague guilt into actionable momentum
  • sharpen payoff framing -> makes incompletion feel worth resolving
  • add cleaner stopping points -> preserves return tension without making the session feel messy
  • reduce nagging visibility for low-value loops -> lowers manipulative pressure

Response structure

Use this structure unless the user asks for something else:

Audit Target

  • ...

Open-Loop Profile

  • ...

Tension Type and Quality

  • ...

Clarity and Resume Path

  • ...

Clutter and Coercion Risks

  • ...

Audience Sensitivity

  • ...

Recommendations

  1. ...
  2. ...
  3. ...

Minimal Fix

  • ...

Fast mode

Use this quick pass when speed matters:

  • What is being left unfinished?
  • Does that create curiosity, momentum, guilt, or clutter?
  • Does the player know how to resume it?
  • Are there too many open loops at once?
  • What one change would make the unfinished tension healthier?

Usage notes

This audit is especially useful for:

  • quest logs
  • event tracks
  • collection systems
  • cliffhanger-driven retention loops
  • city-building and crafting goals
  • return-player re-entry
  • social obligation systems
  • progression dashboards
  • puzzle chains and interrupted runs

Common patterns to watch for:

  • many retention systems misuse open loops and create obligation instead of desire
  • incomplete tasks are powerful only when they are legible and meaningful
  • too many open loops destroy the benefit of any single one
  • a strong unresolved hook can improve return motivation, but a junk drawer of unresolved hooks kills it
  • if the player leaves thinking "I should go back," that may be good; if they leave thinking "ugh, I have chores waiting," that is not

Working principle

Unfinishedness is a tool, not a virtue.

Use this skill to test whether the design leaves players with compelling momentum or just a backpack full of psychological clutter.


Part of the Game Design Skills Bundle by Stanislav Stankovic. Licensed under PolyForm Noncommercial 1.0.0 — free for personal, academic and nonprofit use. Commercial use requires a licence, sold as skill packs. See https://github.com/Stanestane/game-design-skills-bundle for terms.

Required Notice: Copyright Stanislav Stankovic (https://www.stane-island.net/)

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 Game Design Zeigarnik Effect Audit AI skill do?

Audit a game, feature, task system, quest flow, event track, puzzle chain, progression layer, or return loop through the lens of the Zeigarnik effect: the tension created by incomplete, interrupted, or unresolved tasks. Use when evaluating whether a design creates healthy return motivation through open loops, whether it leaves players with productive unfinished business, or whether it turns incompletion into anxiety, clutter, guilt, or manipulative pressure.

Why use Game Design Zeigarnik Effect Audit on TypingMind?

Because you install it once and use it with any model. Game Design Zeigarnik Effect Audit 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 Game Design Zeigarnik Effect Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Stanestane/game-design-skills-bundle/tree/master/game-design-zeigarnik-effect-audit. 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 Game Design Zeigarnik Effect Audit?

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 Game Design Zeigarnik Effect Audit?

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

Is the Game Design Zeigarnik Effect Audit AI skill free?

It is published on GitHub by Stanestane. 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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