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-evergreen-variation-roadmapgit 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-evergreen-variation-roadmap)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-evergreen-variation-roadmap"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-evergreen-variation-roadmap/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-evergreen-variation-roadmap"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-evergreen-variation-roadmap.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 | $0.00058 | $0.01148 |
| Opus 5 | $0.00029 | $0.00574 |
| Sonnet 5 | $0.00012 | $0.00230 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
sealeap-xiezhi-amazon-evergreen-variation-roadmap 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 长期变体路线图
目标
通过真实、合规且有独立需求的子体持续扩展产品线，同时把每个变体当作独立经济单元管理。
适用任务
- 判断产品是否适合长期加变体。
- 规划主题/图案/颜色的年度扩展。
- 为每个子体设计独立关键词、库存与广告。
开始前要拿到
- 当前 product type 与实时允许的 variation theme。
- 每个候选子体的真实属性、图片、SKU、库存和 GTIN 状态。
- 主题/元素的需求、关键词、IP 与季节证据。
- 父体及子体的销量、评论、退货和广告表现。
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。
- 禁止虚假、占位、重复或不相关子体。
- 禁止通过拆分、合并或移除子体规避差评、共享不相关评论或操纵排名。
工作流
1. 验证结构资格
确认产品本质相同且差异完全符合当前类目允许主题；不符合则使用独立 Listing。
2. 建立元素雷达
从季节、活动、风格、图案、颜色和人群需求形成候选，但先做文化与 IP 筛查。
3. 逐子体验证
为每个子体单独核验精准词、竞品、价格、成本、需求和可达销量。
4. 制定发布节奏
按供应链小批能力和需求窗口排序，一次发布有限数量并设置停止条件。
5. 独立经营
每个子体维护准确图片、属性、库存和适用广告；按真实表现补货或停产。
6. 父体健康审计
监控共享体验、评分、退货和选择复杂度；不通过拆并子体操纵评论或排名。
判断标准
- 一个父体真正贡献流量的子体可能有限，不能因共享关系无限扩张。
- 可小批定制和低换款成本是适用条件，但仍需验证每个子体需求。
- 历史评论共享只在合法真实变体关系下发生，不能作为设计变体的目的。
第三方 MCP 数据
需要外部关键词、竞品、评论或公开网页证据时，读取 references/mcp-data-plan.md，并使用 scripts/mcp_research.py。
- 先动态执行
tools/list、search-tools和describe，依据实时inputSchema构造参数。 - 凭证只从环境变量读取，不进入参数、URL、Skill、终端输出或 Git。
- 可能计费的
tools/call先展示 Provider、工具、无密钥参数、预计成本与输出位置，核对已有授权；仅在授权覆盖本次范围时使用--allow-cost，该标志不是费用上限。 - 脱敏结果用
--output写入 Skill 包之外的任务私有目录；不假设安装位置受仓库.gitignore保护。第三方数据标为估算或代理证据。 - 失败一次后记录缺口，不以重复付费重试掩盖不可用状态。
必须交付的结果
- 变体资格矩阵
- 元素/主题雷达
- 子体商业卡
- 发布与淘汰路线图
- 父体健康监控
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
4 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 · 90 lines · 58 tokens per session scan A 53d15294a662
sealeap-xiezhi-amazon-evergreen-variation-roadmap is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 6d ago), licensed MIT. It adds 58 tokens to every session and 1,148 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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