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 thaolst/ai-growth-prompts --skill 03-game-mechanicsgit clone --depth 1 https://github.com/thaolst/ai-growth-promptsWrote 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/thaolst/ai-growth-prompts/03-game-mechanics)<a href="https://agentmods.dev/skills/thaolst/ai-growth-prompts/03-game-mechanics"><img src="https://agentmods.dev/badge/skills/thaolst/ai-growth-prompts/03-game-mechanics/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/thaolst/ai-growth-prompts/03-game-mechanics"><img src="https://agentmods.dev/badge/skills/thaolst/ai-growth-prompts/03-game-mechanics.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 | $0.00000 | $0.02026 |
| Opus 5 | $0.00000 | $0.01013 |
| Sonnet 5 | $0.00000 | $0.00405 |
| Haiku 4.5 | $0.00000 | $0.00203 |
Grade A, and why
03-game-mechanics 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 12d 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 — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
03 · Game mechanics & tương tác
Game và engagement mechanic - thường dùng nhất ở cấp M, nơi ngân sách hỗ trợ độ phức tạp. Ở cấp S, mechanic cần đơn giản và tự hoạt động được trong in-app.
Prompt 07 · Thiết kế game mechanic theo cấp độ
Khi nào dùng: Cần xây hoặc đề xuất game mechanic. Ở cấp M (ngân sách lớn hơn, kênh paid), mechanic phức tạp hơn khả thi. Ở cấp S, phải đủ đơn giản để chạy chỉ với in-app.
Cần thiết kế game mechanic cho loyalty program.
Cấp độ: [S / M / L / XL]
Ngân sách: [ước lượng]
Ràng buộc cấp độ:
- S: mechanic phải chạy hoàn toàn trong app, không có paid reach,
asset = content + design (không concept creative)
- M: có thể thêm 1–2 kênh paid để kéo user vào,
có comm planning và media layer
Bối cảnh:
- Hiện có gì: [mô tả game hoặc tính năng hiện tại]
- Tỉ lệ tương tác hiện tại: [% MAU tương tác mỗi tháng]
- Vấn đề chính: [vd: user vào một lần rồi không quay lại /
chỉ redeem, không chơi game]
- Ràng buộc: [vd: không có dev sprint lớn /
phải launch trong prep timeline của cấp độ này]
Audience mục tiêu:
- [Họ là ai và hành vi hiện tại]
Đề xuất:
1. 3 mechanic - phù hợp độ phức tạp của [S/M]
S: đơn giản, in-house creative làm trong 3–6 tuần
M: có thể layered hơn, supported by comm planning
2. Mỗi mechanic: user flow, return loop, chi phí điểm ước tính
3. Mechanic nào phù hợp nhất với cấp độ và audience - tại sao
4. Rủi ro và cách giảm thiểu trong ràng buộc của cấp độ
5. Metrics theo dõi ở ngày 14 và ngày 30
Prompt 08 · Tìm friction trong game đang chạy
Khi nào dùng: Game đã live, engagement thấp hơn kỳ vọng, cần chẩn đoán nhanh.
Cấp độ game: [S / M / L / XL]
Funnel:
Bước 1 – [tên]: [users / %]
Bước 2 – [tên]: [users / %]
Bước 3 – [tên]: [users / %]
Hoàn thành: [users / %]
Bối cảnh:
- Thời gian trung bình từ vào đến hoàn thành: [nếu biết]
- Session length: [ngắn / vừa / dài]
Phân tích:
1. Bước nào mất nhiều user nhất?
2. 3 giả thuyết - cụ thể cho mechanic, không chung chung
3. Test nhanh nhất cho mỗi giả thuyết trong ràng buộc [S/M]:
- S: đổi copy / điều chỉnh reward / đơn giản hóa flow (không paid boost)
- M: có thể test với paid traffic push để cô lập biến
4. Quick win trong tuần này không cần dev change lớn?
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 217 lines · 0 tokens per session scan A 74a5b0687c96
03-game-mechanics is a skill published in the GitHub repository thaolst/ai-growth-prompts (11 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,026 tokens. 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 2026-08-30.
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