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Balance game difficulty, resources, rewards, probability, progression, economies, and dominant strategies.
Passed 20 of 25 test cases with the skill, and 3 of 25 without it.
and 26 more in the full report
18 fixed2 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 18 test cases the skill fixed. Same model, same prompt, with and without the skill.
Our sci-fi crafting game is having major inflation issues where players hoard titanium and ignore high-tier recipes. We need a complete rebalance proposal for the crafting loop. Please outline the overall emotional and strategic experience we want to cultivate, diagram all currency sinks and sources with their conversion paths, create a parameter adjustment matrix listing default values and safe bounds, analyze potential exploits or dominant playstyles, and set up a validation process with playtesting and telemetry checks.
| Checked | Without skill | With skill |
|---|---|---|
| Includes an explicit Risk Review section that evaluates accessibility concerns. | Missed | Passed |
| Includes script checks in the Validation Plan. | Missed | Passed |
| Includes spreadsheet checks in the Validation Plan. | Missed | Passed |
The instructions your model reads when the skill loads.
Use this skill when a game system needs numerical tuning. Balance is not just fairness; it is the shape of player decisions over time. A good balance pass names the intended experience before changing numbers.
Primary source: The Art of Game Design: A Book of Lenses, Third Edition by Jesse Schell, especially chapters 12-13 on chance, expected value, fairness, challenge, meaningful choices, rewards, punishment, and economies. The workflow is transformed and paraphrased.
Supporting sources include MDA for reasoning from mechanics to dynamics and accessibility guidance for difficulty options that preserve player agency.
Balance Intent: what the numbers should make players feel and do.Economy Map: sources, sinks, currencies, rewards, gates, and conversion rates.Tuning Table: parameters, default values, safe ranges, and intended effects.Risk Review: dominant strategies, exploits, fairness issues, and accessibility concerns.Validation Plan: spreadsheet checks, script checks, playtest tasks, and telemetry.Use scripts/expected_value.py for quick expected value checks:
python3 path/to/game-balance-economy/scripts/expected_value.py --outcome 0:0.5 --outcome 10:0.5
Before producing a tuning plan, read:
references/core/guide.mdworkflows/tuning-pass.mdtest cases passed, vs 3 / 25 without
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