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 01-voucher-designgit 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/01-voucher-design)<a href="https://agentmods.dev/skills/thaolst/ai-growth-prompts/01-voucher-design"><img src="https://agentmods.dev/badge/skills/thaolst/ai-growth-prompts/01-voucher-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/thaolst/ai-growth-prompts/01-voucher-design"><img src="https://agentmods.dev/badge/skills/thaolst/ai-growth-prompts/01-voucher-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 | $0.00000 | $0.01857 |
| Opus 5 | $0.00000 | $0.00928 |
| Sonnet 5 | $0.00000 | $0.00371 |
| Haiku 4.5 | $0.00000 | $0.00186 |
Grade A, and why
01-voucher-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 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
01 · Thiết kế voucher
Thiết kế voucher phù hợp với segment user và cấp độ campaign. Ở cấp S, ít kênh hơn đồng nghĩa mechanic voucher phải tự thân vận động.
| Cấp độ | Kênh | Phạm vi voucher |
|---|---|---|
| S | In-app + owned | 1–2 loại, trigger đơn giản |
| M | Thêm 1–2 kênh paid | 3–5 loại, A/B test được |
| L | Full channels, agency | Multiple sets, creative concept riêng |
Prompt 01 · Thiết kế bộ voucher cho một segment
Khi nào dùng: Đã xác định segment và cấp độ campaign. Cần thiết kế voucher phù hợp.
Cần thiết kế bộ voucher cho campaign loyalty.
Cấp độ campaign: [S / M / L / XL]
Nếu S: chỉ in-app + owned out-app
Nếu M: thêm [kênh paid cụ thể]
Nếu L / XL: bạn cung cấp brief concept - agency thiết kế
Hồ sơ segment:
- Số dư điểm: [thấp / trung bình / cao]
- Tần suất giao dịch: [vd: 1–2 lần/tháng]
- Hành vi gần đây: [vd: đã dùng voucher food, chưa dùng game]
- Số ngày từ lần cuối hoạt động: [số]
Mục tiêu với segment này:
- [vd: kéo user lapsed quay lại / tăng tần suất redeem /
kích hoạt lần đầu]
Ngân sách voucher mỗi user: [ước lượng / hoặc "hẹp / vừa / linh hoạt"]
Đề xuất:
1. 3 phương án voucher - phù hợp segment và phạm vi kênh của cấp độ đó
(cấp S: voucher tự hoạt động được, không cần paid reach)
2. Tại sao từng phương án phù hợp với hành vi segment
3. Logic trigger - gửi khi nào, qua kênh nào
4. Cách đo hiệu quả ở ngày 7 và ngày 14
Prompt 02 · Chọn giữa các hướng voucher
Khi nào dùng: Có 2–3 hướng, cần chọn nhanh.
Đang chọn giữa các hướng voucher cho campaign [S / M / L / XL].
Phương án A: [mô tả ngắn]
Phương án B: [mô tả ngắn]
Phương án C: [nếu có]
Ràng buộc cấp độ:
- S: chỉ in-app + owned, copy + design, timeline gấp
- M: thêm 1–2 kênh paid và comm planning
KPI chính: [vd: redemption rate / tái tương tác / lần đầu giao dịch]
Rủi ro cần tránh: [vd: ăn thịt user đang active / dễ bị abuse]
Yêu cầu:
1. Phương án nào phù hợp nhất với ràng buộc cấp độ và KPI? Tại sao?
2. Điều gì không khả thi ở cấp S nhưng khả thi ở cấp M?
3. Chốt 1 phương án, kèm lý do rõ ràng.
What ships with it
1 file 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 · 204 lines · 0 tokens per session scan A 526da732dafa
01-voucher-design 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 1,857 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.
Other skills, from other repositories
voucher-mechanic-designer
Design and optimize voucher/cashback mechanics for growth campaigns. Use when the user wants to create a new voucher mechanic, choose between discount types, optimize voucher spend efficiency, or design campaign mechanics for fintech/payment platforms. Specialized for SEA fintech.
tbank-grocery-order
A skill that guides grocery orders through T-Bank's City service, from choosing products to checkout and payment.
tbank-tickets
Instructions for buying cinema, concert, theatre, and exhibition tickets through T-Bank's event service. They cover the process from finding an event and checking seats to making a paid booking.
ecom-applicability
Determine whether AI is appropriate for a specific e-commerce task. Use when evaluating if a problem has enough data, the right tools, or acceptable risk for AI automation. Answers 'should I use AI for X?' with boundary-aware reasoning.
ecom-social
Instructions for creating and improving e-commerce social-media content, advertising, and community work across platforms such as Instagram, YouTube, TikTok, Pinterest, Reddit, WhatsApp, and Xiaohongshu.
ecom-advertising
Diagnose and optimize Amazon PPC campaigns. Use for ACOS analysis, bid optimization, keyword harvesting, campaign structure, or multi-marketplace advertising.