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Game Design Leaderboard Audit

Community
Stanestane
game-design-leaderboard-audit

Audit an existing leaderboard or competitive ranking system in a game for stagnation risk, scale problems, goal density, motivation quality, reward bracket design, group composition fairness, and top-of-ladder sustainability. Use when evaluating a leaderboard that feels flat, unfair, or disengaging; when reviewing a competitive feature before launch; or when diagnosing why a leaderboard isn't driving expected engagement or retention.

Overview

PublisherStanestane
Repositorygame-design-skills-bundle
Skill namegame-design-leaderboard-audit
Stars
87
Forks
18
Bundled files
Instructions only
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 Stanestane on GitHub. Read the source before you install it.

Installation

Install the Game Design Leaderboard 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-leaderboard-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-leaderboard-audit .claude/skills/game-design-leaderboard-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Game Design Leaderboard 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 Leaderboard 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 Leaderboard 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 Leaderboard Audit

Audit a leaderboard or competitive ranking system as a metagame feature — not just as a list, but as a system that generates goals, competition, and emotional investment for the majority of players.

Use this skill to evaluate whether a leaderboard is actually doing its job. A leaderboard that only matters to the top 10 players has failed. The audit focuses on seven dimensions: stagnation, scale, goal density, motivation, reward brackets, group composition, and the top-of-ladder problem.

Core principle

A leaderboard is the start of a metagame. Its quality is not measured by whether it ranks players — it is measured by whether it generates meaningful, emotionally resonant competition for the majority of the player base, from the player at the very top to the player sitting in the middle of a group of 100.

What to produce

Generate:

  1. Audit target — what is being reviewed and what context it sits in
  2. Stagnation audit — whether the leaderboard feels alive or frozen
  3. Scale audit — whether the numbers are human-meaningful
  4. Goal density audit — how many distinct goals the structure generates
  5. Motivation audit — the quality and balance of intrinsic vs. extrinsic motivation
  6. Reward bracket audit — coverage, fairness, and value calibration
  7. Group composition audit — fairness and competitive integrity
  8. Top-of-ladder audit — what happens when a player reaches the ceiling
  9. Failure patterns — named anti-patterns present in the design
  10. Recommendations — prioritized, specific, actionable

Process

1. Define the audit target

Clarify:

  • What game, feature, or competitive system is being audited
  • What the score or ranking metric is
  • Whether this is a global list, a group-based system, or a league ladder
  • What the competition round length is (if any)
  • What rewards or consequences are attached to standings
  • What stage the design is at: concept, in production, live

If details are incomplete, note what is assumed and flag it.

2. Stagnation audit

The most damaging leaderboard failure is invisibility — a board nobody checks because nothing ever moves.

Ask:

  • What is the score, and how frequently does it change?
  • Can the score change meaningfully during a single play session?
  • Does the score reset at any point, or is it purely cumulative?
  • Could a player who starts today ever catch a veteran at the same skill level?
  • How long would it take to move one position at the median rank?

Look for:

  • Lifetime-accumulated scores with no reset (permanent head-start advantage)
  • Scores that change only once per day or slower
  • Score granularity too coarse to show movement (e.g., everyone stuck at round numbers)
  • No mechanism for new players to enter competitive positions

Label the finding:

  • Healthy — score changes multiple times per session; leaderboard visibly shifts
  • Borderline — score changes daily; some movement is visible over a week
  • Stagnant — score changes slowly or reflects lifetime play; board rarely shifts
  • Dead — lifetime score, no reset, veterans permanently untouchable

3. Scale audit

Ask:

  • How many players are ranked in a single visible leaderboard?
  • What position would a median-skill new player typically occupy?
  • Are the position numbers emotionally meaningful? (Position 156,342 is not.)
  • Does the leaderboard show the player's own position relative to others nearby?
  • Is the competition scope global, regional, or grouped?

Look for:

  • Global leaderboards with tens of thousands of entries
  • Position numbers too large to parse emotionally
  • No visible neighborhood (the players just above and below the viewer)
  • Leaderboard that only highlights top 10 while ignoring everyone else

Evaluate: does the player feel like they are in a real, contestable race — or watching a scoreboard from a distance?

4. Goal density audit

A well-designed leaderboard generates multiple simultaneous goals at different time scales. Evaluate whether this structure provides all three tiers:

Immediate goal — overtake the player directly above me (next session) Short-term goal — climb several places or reach the next reward bracket (this week) Medium-term goal — earn promotion to the next league (this round) Long-term aspirational goal — reach the top of the ladder (months)

Ask:

  • Does the structure create all four goal tiers naturally?
  • Is the immediate goal always visible and achievable for a player of average commitment?
  • Is the long-term goal aspirational without feeling impossible?
  • Does the reward bracket design create additional intermediate goals between the goal tiers?
  • Are demotion stakes generating meaningful tension at the bottom of the leaderboard?

Use this format:

Goal tierPresentStrengthMain gap
Immediate (overtake neighbor)Yes / No......
Short-term (climb / reach bracket)Yes / No......
Medium-term (promotion)Yes / No......
Long-term aspirational (top of ladder)Yes / No......

5. Motivation audit

Ask:

  • What intrinsic motivation does the structure create? (pride, prestige, mastery, social competition)
  • What extrinsic motivation does the structure create? (rewards, currencies, exclusive content)
  • Is either type absent or over-dominant?
  • Does the design feel like genuine competition, or does it feel like a chore with prizes?
  • Could a player who receives no rewards still find the leaderboard engaging?
  • Does the reward structure create pressure and anxiety, or anticipation and excitement?

Evaluate balance:

  • Intrinsic only — sustainable for hardcore players, will fail to retain casual players
  • Extrinsic only — drives short-term behavior, creates burnout and pay-to-win perception
  • Balanced — leaderboard climbing feels worth doing for its own sake; rewards amplify rather than justify

6. Reward bracket audit

Ask:

  • Are reward brackets defined? How many brackets exist?
  • What percentage of players receive a meaningful reward?
  • Is the consolation bracket wide enough to reward participation without trivializing achievement?
  • Is the top bracket sufficiently rare and prestigious?
  • Are mid-tier brackets spaced to create meaningful distinctions between them?
  • What happens to players who finish outside all brackets — do they feel their effort was wasted?
  • Are rewards appropriate to the effort required to reach each bracket?

Evaluate coverage:

  • Too narrow — only top 3-5 players rewarded; the system ignores 95% of participants
  • Too wide — everyone gets a reward; prestige collapses
  • Healthy — meaningful rewards for top ~20-30%; consolation tier for ~30-50%; nothing for bottom ~20-30%

7. Group composition audit

Ask:

  • How are players assigned to groups?
  • Are new players mixed with long-term veterans?
  • Are high spenders mixed with free players in the same group?
  • Is there any skill or activity matching, or is grouping random?
  • What happens if a highly active player is permanently dominant in their group?
  • Are there mechanisms to refresh or rebalance groups?

Look for:

  • Whale-dominated groups — one spender makes everyone else irrelevant; destroys motivation for the whole group
  • Sandbagging risk — players deliberately losing to stay in a weaker league; reward structure incentivizes this
  • Static groups — same players compete forever; competition becomes predictable and stale
  • No catch-up — players with early-round leads become untouchable by mid-round; others disengage

8. Top-of-ladder audit

Ask:

  • What happens to a player who reaches the top position in the top league?
  • Does the game have an answer for elder players with nowhere left to climb?
  • Is the top league expanding over time, or is it a fixed ceiling?
  • Are naming conventions for league tiers scalable, or will they become absurd?
  • What sustains engagement for the most competitive players after they have "won"?

Common failure shapes:

  • The empty summit — player reaches the top, loses all leaderboard motivation
  • Name exhaustion — Gold → Platinum → Diamond → Obsidian → what next?
  • Inflation — the top league grows until prestige disappears
  • Reset shock — periodic resets exist but were introduced after launch; veteran backlash

9. Diagnose failure patterns

Name and describe each present anti-pattern:

  • Stagnant board — score moves too slowly; nobody checks the leaderboard
  • Scale blindness — position numbers are too large to feel meaningful
  • Goal poverty — the structure generates only one or two goals instead of a ladder of them
  • Reward desert — most players finish a round with nothing; effort feels wasted
  • Reward flood — everyone gets something; prestige disappears
  • Whale capture — one dominant player destroys the competitive dynamic for the whole group
  • Global vanity board — a list that is technically a leaderboard but creates no real competition
  • Empty summit — no design answer for players who have reached the top
  • Chore motivation — rewards justify participation; without them, no one would care
  • Sandbagging loop — reward structure makes intentional losing rational

10. Convert findings into recommendations

For each significant issue:

  • Issue — what is wrong
  • Why it hurts — specific player experience or metric impact
  • Fix direction — what structural change addresses it
  • Priority — Critical / Important / Polish

Response structure

Audit Target

  • ...

Stagnation

  • Verdict: Healthy / Borderline / Stagnant / Dead
  • Findings: ...

Scale

  • ...

Goal Density

  • Table: ...
  • Gaps: ...

Motivation

  • Intrinsic: ...
  • Extrinsic: ...
  • Balance verdict: ...

Reward Brackets

  • Coverage: Too narrow / Healthy / Too wide
  • Issues: ...

Group Composition

  • ...

Top-of-Ladder

  • ...

Failure Patterns

  • ...

Recommendations

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

Fast mode

If the user provides a quick description and wants a rapid read:

  • Is the score fast-changing or lifetime-accumulated?
  • Is this global or grouped? If global, how many players?
  • Does it reward anyone below position 10?
  • What happens to a player in the middle of the board — do they have something to play for?
  • What happens to the player at the very top?

Working principle

A leaderboard that only matters to the top ten players is a monument, not a feature. The audit's job is to find how many players the design is failing — and why.


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/)

Frequently asked questions

What does the Game Design Leaderboard Audit AI skill do?

Audit an existing leaderboard or competitive ranking system in a game for stagnation risk, scale problems, goal density, motivation quality, reward bracket design, group composition fairness, and top-of-ladder sustainability. Use when evaluating a leaderboard that feels flat, unfair, or disengaging; when reviewing a competitive feature before launch; or when diagnosing why a leaderboard isn't driving expected engagement or retention.

Why use Game Design Leaderboard Audit on TypingMind?

Because you install it once and use it with any model. Game Design Leaderboard 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 Leaderboard 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-leaderboard-audit. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Game Design Leaderboard 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 Leaderboard Audit?

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

Is the Game Design Leaderboard 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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