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 xjli360/sealeap-amazon-ad-skills --skill sealeap-xiezhi-amazon-scalable-product-portfolio-modelgit clone --depth 1 https://github.com/xjli360/sealeap-amazon-ad-skillsWrote 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/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-scalable-product-portfolio-model)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-scalable-product-portfolio-model"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-scalable-product-portfolio-model/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/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-scalable-product-portfolio-model"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-scalable-product-portfolio-model.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 | $0.00054 | $0.00900 |
| Opus 5 | $0.00027 | $0.00450 |
| Sonnet 5 | $0.00011 | $0.00180 |
| Haiku 4.5 | $0.00005 | $0.00090 |
Grade A, and why
sealeap-xiezhi-amazon-scalable-product-portfolio-model 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 5d 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.
What it actually says
Amazon 可复制产品组合模式
目标
把单条链接的偶然成功转化为可复制的选品、供应链、推广、补货和淘汰系统，并控制单品依赖风险。
适用任务
- 比较爆款集中模式与分散盈利组合。
- 判断一次成功是否可以复制。
- 为中小团队设计由流程驱动的扩张路线。
开始前要拿到
- 收入与利润对 SKU 的集中度。
- 爆款形成原因、可持续性和对关键个人的依赖。
- 新品开发、首批库存、广告、补货和淘汰的历史结果。
- 团队角色、SOP 完整度、现金流与最坏情景承受力。
缺少字段时列出证据缺口，并把相关结论标为 FACT、ESTIMATE、ASSUMPTION 或 UNKNOWN；不要补造数据。
不可妥协的边界
- 第三方数据均为估算或代理证据；Amazon 一方报告、后台实时字段和产品事实优先。
- 经验阈值只能作为可调起点，必须展示敏感性分析，不能写成 Amazon 官方规则。
- 不得捏造销量、搜索量、CPC、CVR、成本、认证、产品属性或消费者需求。
- 默认提供诊断或草案。写入前展示对象、旧值、新值、影响、停止线与回退，核对用户已有授权是否覆盖对象、动作与预算；范围已明确授权时继续执行并回读核验，只有未覆盖或扩大的范围才请求批准。
- 不输出或保存素材来源身份、账号、链接、作品编号、互动数据、原始话术或其他可反查来源的线索。
- 不得把分散 SKU 理解为无差别铺货。
- 不得用违规评价、变体或流量手段换取短期可复制假象。
工作流
1. 拆解成功
把一次产品成功分解为市场选择、差异化、供应链、定价、广告、库存和时机，区分可复制能力与偶然红利。
2. 量化集中风险
计算头部 SKU 收入/利润占比，模拟单条链接下滑、断货或账户事件对公司的影响。
3. 设计组合
用少量增长款拉升订单、更多稳定款贡献利润，并为每类产品定义投入、退出和补货规则。
4. 固化流程
把市场分析、供应商筛选、首批备货、广告测试、补货和淘汰写成普通成员可执行的检查表。
5. 分阶段复制
先验证流程的多次复现，再增加人员、库存和固定成本；每一档扩张都设置失败回退条件。
判断标准
- 一条链接盈利不等于选品能力或商业模式已验证。
- 真正可复制的是过程、门槛与反馈闭环，不是对某位高手的依赖。
- 低概率但可摧毁账户、库存与现金流的风险必须按高影响事件管理。
必须交付的结果
- 模式对比与选择
- SKU 组合角色表
- 关键人依赖审计
- 阶段扩张门槛
- SOP 与最坏情景回退方案
结尾列出站点、数据窗口、证据来源、关键假设、缺口、风险、下一步和所有待批准动作。证据不足时写 HOLD，不得包装成可直接执行。
执行细节、证据字段和质量检查见 references/playbook.md。
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.
- 5d ago First seen · 76 lines · 54 tokens per session scan A 490ce5d5d26b
sealeap-xiezhi-amazon-scalable-product-portfolio-model is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 6d ago), licensed MIT. It adds 54 tokens to every session and 900 once invoked, about $0.0003 per session on Opus 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 2026-09-07.
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