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-conversion-rate-prelaunch-estimationgit 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-conversion-rate-prelaunch-estimation)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/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-conversion-rate-prelaunch-estimation"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation.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 | $0.00061 | $0.01231 |
| Opus 5.5 | $0.00024 | $0.00492 |
| Sonnet 5.5 | $0.00012 | $0.00246 |
| Haiku 4.5 | $0.00006 | $0.00123 |
Grade A, and why
sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation 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 上市前转化率估算
目标
用头部链接和细分市场两种口径交叉估算转化率，再判断保本 CVR 是否现实。
适用任务
- 测算候选产品的保本转化率。
- 用单 ASIN 与市场整体数据交叉验证。
- 识别长决策、低转化且广告难盈利的市场。
开始前要拿到
- 售价、落地成本、Amazon 费用、优惠和目标利润。
- 精准词 CPC 区间。
- 竞品销量与搜索点击代理数据。
- Amazon 商机探测器或其他一方市场购买率数据。
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。
- 不得把销量估算与点击估算的比值写成真实转化率。
- 当前 Amazon 一方字段定义优先于任何历史方法。
工作流
1. 统一单位经济
计算广告前贡献毛利、盈亏平衡 CPA、ACoS 和所需 CVR，并明确税费、退款和优惠口径。
2. 估单品 CVR
只有订单与点击来自相同流量范围、对象、时间窗和归因口径时才估算订单 CVR。全渠道销量除以搜索点击只能标为需求比例代理，不能作为 CVR 或直接代入 CPA；缺少可比样本时用明确标注的假设区间并保留 HOLD。
3. 估市场 CVR
读取细分市场购买率、转化购买率或等价一方指标，解释访客、点击、归因窗差异。
4. 形成区间
不机械取单点，使用保守/基准/乐观三档并剔除口径不可比样本。
5. 做立项闸门
若头部或市场基准仍低于保本 CVR，则 HOLD；只有差异化能被证据支持时才建立例外情景。
判断标准
- CPA = CPC / 订单 CVR；保本订单 CVR = CPC / 广告前每单贡献毛利。贡献毛利非正、分母为零或所需 CVR 超过 100% 时，标为当前经济模型不可行。
- 搜索点击口径通常不能代表全部流量，单 ASIN 结果必须标注偏差方向。
- 购买率与转化购买率定义可能随报表变化，必须记录当前官方字段说明。
- 头部转化差时，新品默认不能假设显著优于头部。
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
- 单位经济表
- 单 ASIN CVR 区间
- 市场 CVR 区间
- 保本敏感性矩阵
- GO/HOLD/NO-GO 及证据缺口
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 · 87 lines · 61 tokens per session scan A ceedfc0c61fa
sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 1mo ago), licensed MIT. It adds 61 tokens to every session and 1,231 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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