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-large-keyword-portfoliogit 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-large-keyword-portfolio)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-large-keyword-portfolio"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-large-keyword-portfolio/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-large-keyword-portfolio"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-large-keyword-portfolio.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 | $0.00086 | $0.01119 |
| Opus 5.5 | $0.00034 | $0.00448 |
| Sonnet 5.5 | $0.00017 | $0.00224 |
| Haiku 4.5 | $0.00009 | $0.00112 |
Grade A, and why
sealeap-amazon-large-keyword-portfolio 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 大规模关键词组合
目标
扩大相关长尾覆盖的同时控制预算碎片化、自动化误杀和管理复杂度，而不是追求活动数量本身。
适用任务
- 候选关键词很多，需要批量建广告。
- 考虑单词单组或单活动结构。
- 希望用规则自动升价、降价、否定或暂停。
开始前要拿到
- 经验证的关键词主表、词根、意图和搜索量代理。
- 批量表格字段、账号限制、组合预算和命名规范。
- 历史 CPC/CVR、最小样本、止损和审批责任人。
缺失的数据要明确列为缺口，并把结论标成事实、估算或假设；不要补造数字。
不可妥协的边界
- 活动数量没有固定正确值；低流量词可按同质意图聚类，避免无意义碎片化。
- 词根组合生成的查询必须通过真实搜索或相关性证据过滤，不能把机器拼词直接投放。
- 自动规则默认只生成建议；升价、否定和暂停需样本护栏与人工批准。
- 当前 Amazon 官方政策、帮助页、账户资格和后台实际字段优先于本 Skill 中的经验框架；规则可能变化时先核验。
- 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。
- 不输出原素材的创作者身份、账号、链接、视频编号或可反查线索；当前业务证据的官方来源、采集时间和口径仍需保留。
第三方 MCP 数据
只有在本任务确实需要外部市场、竞品、关键词或公开网页证据时，才读取 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，不照搬历史工具名。
- 凭证只从环境变量读取，不放进命令参数、URL、Skill、结果文件或 Git。
- tools/call 可能计费。调用前展示 Provider、工具名、无密钥参数、预计成本与输出位置，核对已有授权覆盖后才加 --allow-cost；该标志不是费用上限。
- 第三方数据标为估算或代理证据，记录 Provider、工具、无密钥参数、查询时间和原始结果位置；失败一次后记录缺口，不反复消耗额度。
- 脱敏结果用 --output 写到 Skill 包之外的任务私有目录；不假设安装位置受仓库 .gitignore 保护，不把运行结果写入 Skill 包。
工作流
1. 清洗候选词
去重并验证真实相关性、购买意图和可读性，删除仅语法成立但无消费者证据的组合词。
2. 决定粒度
高价值或需独立预算的词采用隔离结构；低流量同质词按词根聚类，控制活动数量。
3. 设置预算保护
给产品或组合设置日预算帽、累计测试损失和库存护栏，再分配到各批次。
4. 建立竞价阶梯
按 CPC 先验和利润从保守竞价开始，无曝光时小步上调；每次保留变更日志。
5. 设计安全规则
规则包含最小点击、最小时间、最大单次幅度、冷却期、累计花费和回滚条件。
6. 批量预检
在上传前验证实体 ID、匹配类型、预算、否定冲突和重复覆盖；输出草稿等待批准。
判断标准
- 关键词总数、活动总数和预估最大日花费一致。
- 所有自动规则都有样本与冷却保护。
- 批量文件不含凭证和敏感账号数据。
必须交付的结果
- 关键词清洗与聚类结果。
- 活动粒度和命名方案。
- 预算帽、竞价阶梯和安全规则。
- 待审核批量表格规格。
结尾列出数据窗口、关键假设、证据缺口、风险和下一步；如包含待执行动作，单独放在“待批准变更”中。
What ships with it
3 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 · 85 lines · 86 tokens per session scan A 5b1516502b47
sealeap-amazon-large-keyword-portfolio is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 1,119 once invoked, about $0.0003 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 2026-09-07.
Other skills, from other repositories
zach-search-term-analyzer
An analyzer for Amazon Brand Analytics Top Search Terms reports, which show popular searches across Amazon and how clicks and conversions are distributed among products.
ecom-image2
An image-generation workflow for creating e-commerce visuals with GPT-Image-2, such as product images, banners, social posts, and infographics.
sorftime-seller-agent
Sorftime Seller Agent — Expert-level cross-border e-commerce data analysis and product sourcing intelligence for Amazon, Walmart, TikTok Shop, 1688, Shopee, and TEMU sellers (plus Reddit social-listening queries). A single skill that turns any MCP-enabled AI agent (Claude Code, OpenClaw, Cursor, Copilot) into a…
ai-model-expert-1688-ecommerce-video-generation-editing
An AI tool workflow for creating and editing 1688 e-commerce videos from text, images, videos, or audio. 1688 is a Chinese online wholesale marketplace.
302-ai-alternative-ai-hive
A migration guide for teams moving between AI model API platforms, especially for image and video generation. It helps review an existing OpenAI-compatible integration and plan testing, routing, and fallback options.
ai-hive-agentic-ocr-targeted-evidence
A document-search workflow that first finds likely pages and then uses OCR, or software that reads text from images, on only the relevant scans, tables, or small text.