Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add makifbaysal/tasktrooper --skill data-driven-gameplay-designgit clone --depth 1 https://github.com/makifbaysal/tasktrooperWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/makifbaysal/tasktrooper/data-driven-gameplay-design)<a href="https://agentmods.dev/skills/makifbaysal/tasktrooper/data-driven-gameplay-design"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/data-driven-gameplay-design/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/makifbaysal/tasktrooper/data-driven-gameplay-design"><img src="https://agentmods.dev/badge/skills/makifbaysal/tasktrooper/data-driven-gameplay-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.01607 |
| Opus 5.5 | $0.00029 | $0.00643 |
| Sonnet 5.5 | $0.00015 | $0.00321 |
| Haiku 4.5 | $0.00007 | $0.00161 |
Grade A, and why
data-driven-gameplay-design scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data-Driven Gameplay Design
Overview
Designers balance games by changing numbers hundreds of times. If a number lives in code, each change is a programmer task, a rebuild and a review. If it lives in a data asset, it is an edit a designer can make and a test can check. The code defines what a sword is; the data says what this sword does.
Core principle: Behaviour in code, tuning in data. Data is typed, validated at load, referenced by a stable ID, and never mutated at runtime.
The data asset per engine
// Unity: ScriptableObject definition
[CreateAssetMenu(menuName = "Game/Weapon")]
public sealed class WeaponDefinition : ScriptableObject {
[SerializeField] string id;
[SerializeField, Min(0)] int damage = 10;
[SerializeField, Min(0.05f)] float cooldownSeconds = 0.5f;
[SerializeField] AnimationCurve falloff = AnimationCurve.Linear(0, 1, 1, 0);
public string Id => id; public int Damage => damage; public float CooldownSeconds => cooldownSeconds;
void OnValidate() { if (string.IsNullOrWhiteSpace(id)) Debug.LogError($"{name}: missing id", this); }
}
# Godot: a Resource saved as .tres
class_name WeaponDefinition extends Resource
@export var id: StringName
@export_range(0, 1000) var damage: int = 10
@export_range(0.05, 10.0, 0.05) var cooldown_seconds: float = 0.5
// Unreal: a primary data asset (or an FTableRowBase row in a DataTable imported from CSV)
UCLASS(BlueprintType)
class UWeaponDefinition : public UPrimaryDataAsset {
GENERATED_BODY()
public:
UPROPERTY(EditDefaultsOnly, meta = (ClampMin = "0")) int32 Damage = 10;
UPROPERTY(EditDefaultsOnly, meta = (ClampMin = "0.05")) float CooldownSeconds = 0.5f;
virtual FPrimaryAssetId GetPrimaryAssetId() const override { return FPrimaryAssetId("Weapon", GetFName()); }
};
// Web: JSON validated once at load (zod)
export const Weapon = z.object({
id: z.string().min(1),
damage: z.number().int().nonnegative(),
cooldownSeconds: z.number().min(0.05),
});
export const weapons = z.array(Weapon).parse(await (await fetch("data/weapons.json")).json());
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 128 lines · 73 tokens per session scan A 957f655e5b82
data-driven-gameplay-design is a skill published in the GitHub repository makifbaysal/tasktrooper (113 stars, last pushed yesterday), licensed Apache-2.0. It adds 73 tokens to every session and 1,607 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-09.
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