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-amazon-localization-marketinggit 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-amazon-localization-marketing)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-localization-marketing"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-localization-marketing/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-amazon-localization-marketing"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-localization-marketing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00143 | $0.00954 |
| Opus 5.5 | $0.00057 | $0.00382 |
| Sonnet 5.5 | $0.00029 | $0.00191 |
| Haiku 4.5 | $0.00014 | $0.00095 |
Grade A, and why
sealeap-amazon-localization-marketing 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 1mo 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 本土化营销
目标
将“把英文翻译成目标语言”升级为可追溯的本土化：保留商品事实，重建当地消费者的搜索语言、表达习惯、购买顾虑和场景，再用当前站点规则检查并做小范围实验。
开始前读 references/source-and-guardrails.md。关键词与 Listing 读 references/keyword-and-listing-workflow.md，广告素材读 references/creative-localization-review.md。
工作流
1. 固定源与目标
记录 source marketplace/language、target marketplace/language、ASIN/SKU、product type、变体、发布日期和责任人。源文案不是事实源；另建产品事实表，标出单位、兼容性、材料、认证、警告和不能使用的声明。
2. 建立本地证据
优先使用目标站点的 Brand Analytics、Search Query Performance、Ads 搜索词、自动广告查询、Product Opportunity Explorer、客服/评论主题和当前竞品页面观察。保留来源、日期、站点、指标和样本范围。
第三方搜索量或 AI 建议只标代理证据，不能替代目标站点真实搜索行为。
3. 区分三种处理
TRANSLATE：事实与表达可直接对应；TRANSLOCALIZE：事实不变，但术语、单位、语序、场景和说服方式重写；RECREATE：创意概念不适合当地文化，需要重新 brief。
对每个字段明确采用哪一种，避免全文统一机器翻译。
4. 构建本地关键词图
按核心品类、功能、场景、人群、问题、规格、同义词/口语和季节词分组。记录本地原词、中文释义、证据、意图、建议字段和禁用原因。不要把美国站长尾结构强套到其它站点。
5. 重写 Listing 与广告
先遵循当前 product type/marketplace 的字符、必填字段和禁限词规则，再兼顾可读性与关键词覆盖。标题、五点、描述、A+、后台词和广告文案各自承担不同任务，不重复堆词。
6. 本地化图片与视频
审查画面人物、住宅/道路/插座、单位、日期、手势、色彩、节日、使用方式、字幕/文字、安全警告和 Logo。语言正确不等于文化适配；画面不适配时选择 RECREATE。
7. 三重审核
FACT：没有新增或弱化商品事实与安全信息；NATIVE：由目标语言母语/专业审校确认自然、清楚、有说服力；POLICY：当前 marketplace 的 Listing、Ads、IP 和类目规则。
8. 测试与发布
只测试一个本土化变量，例如标题表达、主图文字层、广告钩子或关键词组。发布前输出逐字段旧值/新值、证据和回退；只有明确批准后才能提交，提交后复读。
必须交付
- source/target 作用域与事实表；
- 本地关键词图及证据等级；
TRANSLATE / TRANSLOCALIZE / RECREATE字段决策；- 本地化文案/创意 brief 与三重审核；
- 一个单变量实验、审批与回退状态。
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.
- 1mo ago First seen · 63 lines · 143 tokens per session scan A e9eb9dff2ee1
sealeap-amazon-localization-marketing is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 1mo ago), licensed MIT. It adds 143 tokens to every session and 954 once invoked, about $0.0006 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 2026-09-04.
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