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 5.5 | $0.00020 | $0.00468 |
| Sonnet 5.5 | $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 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 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.
- 1mo 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 1mo ago), licensed MIT. It adds 49 tokens to every session and 1,169 once invoked, about $0.0002 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.
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