sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation

sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation is a skill for Codex from xjli360/sealeap-amazon-ad-skills. It costs 61 tokens per session (1,231 once invoked), scanned A, original, MIT.

A pre-launch research method for estimating a realistic range of Amazon conversion rates and checking whether a product can break even. Conversion rate means the share of visitors or clicks that become orders.

In plain words
What is it for?
Use it to calculate break-even conversion rates, compare one product with the wider market, model conservative and optimistic cases, and decide whether to launch or pause.
Why use it?
Teams can otherwise approve a product only because its profit model assumes an untested conversion rate. This method exposes differences between product-level data, market data, and traffic sources.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to calculate break-even conversion rates, compare one product with the wider market, model conservative and optimistic cases, and decide whether to launch or pause.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation
Install

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.

Any agent
npx skills add xjli360/sealeap-amazon-ad-skills --skill sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation
Clone the repo
git clone --depth 1 https://github.com/xjli360/sealeap-amazon-ad-skills

Made for: Codex.

Wrote 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.

agentmods badge for sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation

README.md
[![agentmods](https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/github.svg)](https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation)
Your own site
<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.

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Your own site · 80×15
<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>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,231 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00061 $0.01231
Opus 5 $0.00030 $0.00616
Sonnet 5 $0.00012 $0.00246
Haiku 4.5 $0.00006 $0.00123

Measured 5d ago against content hash ceedfc0c61fa, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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 5d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/mcp_research.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation/SKILL.md · 87 lines

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 FACTESTIMATEASSUMPTIONUNKNOWN;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/listsearch-toolsdescribe,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

Files

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.

Changes

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.

  1. 5d ago First seen · 87 lines · 61 tokens per session scan A ceedfc0c61fa

Subscribe to this mod's changes

sealeap-xiezhi-amazon-conversion-rate-prelaunch-estimation is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 6d ago), licensed MIT. It adds 61 tokens to every session and 1,231 once invoked, about $0.0003 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.

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