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-profit-bound-ad-operationsgit 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-profit-bound-ad-operations)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-profit-bound-ad-operations"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-profit-bound-ad-operations/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-profit-bound-ad-operations"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-profit-bound-ad-operations.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 | $0.00049 | $0.01169 |
| Opus 5 | $0.00024 | $0.00584 |
| Sonnet 5 | $0.00010 | $0.00234 |
| Haiku 4.5 | $0.00005 | $0.00117 |
Grade A, and why
sealeap-xiezhi-amazon-profit-bound-ad-operations 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 盈利边界广告运营
目标
从选品阶段就限定精准流量和可承受点击，用小型广告结构寻找每个 SKU 的盈利流量区间，并及时降级失败品。
适用任务
- 为低库存多 SKU 模式设计广告。
- 在流量增大但转化下降时守住利润。
- 决定 SKU 是放大、维持、降级还是停投。
开始前要拿到
- SKU 级售价、贡献毛利、库存和销售目标。
- 精准词及其搜索意图、建议竞价和 Listing 覆盖。
- 广告活动/搜索词/广告位的 CPC、CVR、CPA、ACoS 与订单。
- 自然排名、总订单、补货时效和止损上限。
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。
- 不得以广告掩盖产品、价格、库存或页面根因。
- 任何投放、竞价、预算、否定或暂停操作先获明确批准。
工作流
1. 设盈利边界
计算保本 CPC、CPA 和 ACoS，并为目标利润留安全余量。
2. 精简结构
每个活动放少量同意图词；大流量词必要时独立，确保预算和结果可归因。
3. 控制学习
预算覆盖预设样本即可，不追求大量流量；记录归因窗和累计亏损。
4. 先调位置
样本充分后比较广告位，再通过基础竞价与位置系数让流量向高质量位置倾斜。
5. 再调词
高相关低效词隔离复测，不相关词否定，已验证查询从广泛迁入精准。
6. 管理 SKU 状态
盈利且可补货的放大；接近边界的维持；长期不可盈利的降级到低投入或停止。
判断标准
- 每日约 20–30 次点击或一至两周观察只是样例，样本应由预期 CVR、预算和损失上限决定。
- 流量增加后 CVR 下滑可能来自查询/广告位变化，不能直接归因于隐藏人群配额。
- 广告目标是贡献利润与可持续周转，不是单独追求 BSR 或最低 ACoS。
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
- SKU 盈利边界表
- 精简活动结构
- 广告位/查询诊断
- 放大/维持/降级状态
- 待批准最小变更集
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 · 49 tokens per session scan A efbb042ff6e6
sealeap-xiezhi-amazon-profit-bound-ad-operations is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 6d ago), licensed MIT. It adds 49 tokens to every session and 1,169 once invoked, about $0.0002 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.
Other skills, from other repositories
zach-seller-skill-creator
A Chinese-language guide for Amazon sellers who want to turn repeated work processes into reusable skills for an AI agent.
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.
zach-search-term-report-analyzer
An Amazon Ads search-term report analyzer for Sponsored Products, Sponsored Brands, and Sponsored Display campaigns. It groups related search terms, measures results over 7, 14, and 30 days, and produces reports in several file formats.
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…
amazon-analysis
Amazon-domain general analysis and multi-endpoint research engine. Handles broad or composite Amazon research requests that span multiple data dimensions or have no single specialized angle. Use when: - user asks for multi-endpoint Amazon research, composite reports, or general Amazon market/product analysis user asks…
amazon-market-trend-scanner
Amazon category trend scanner. Scans Amazon category landscapes to discover trending subcategories, emerging niches, and market shifts. Tracks demand surges, brand consolidation, new entrant waves, price band migration, and margin changes across all subcategories under a parent category. Use when user asks about…