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-operator-to-owner-readinessgit 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-operator-to-owner-readiness)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-operator-to-owner-readiness"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-operator-to-owner-readiness/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-operator-to-owner-readiness"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-amazon-operator-to-owner-readiness.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 | $0.00077 | $0.00867 |
| Opus 5.5 | $0.00031 | $0.00347 |
| Sonnet 5.5 | $0.00015 | $0.00173 |
| Haiku 4.5 | $0.00008 | $0.00087 |
Grade A, and why
sealeap-amazon-operator-to-owner-readiness 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 运营创业准备度
目标
识别“会运营”与“能经营完整生意”之间的差距，先验证现金流、产品组合和全盘能力再决定是否独立。
适用任务
- 运营准备离职创业。
- 独立后新品成功率低、现金紧张或固定成本过高。
- 比较不同站点、商品类型和低固定成本模式。
开始前要拿到
- 个人与团队能力、可使用但不侵权的资源、时间和风险偏好。
- 启动资金、固定支出、生活备用金、供应链账期和回款周期。
- 候选商品单位经济、失败概率、补货和退出成本。
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
- 不得带走前雇主的账号、数据、客户、供应商机密、代码或知识产权。
- 不把过去在公司获得的成绩等同于独立经营成功率。
- 不建议用生活必需资金或不可承受债务支撑高风险验证。
- 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。
工作流
1. 拆分能力栈
分别评估选品、采购、财务、合规、广告、库存、客服和团队管理，找出过去由公司承担的部分。
2. 建立资金时间线
把公司注册、样品、生产、运输、入仓、推广、退货和回款排在同一现金流线上。
3. 建模组合成功率
根据单品验证成本和保守成功率估算需要多少候选品、总资金和时间，避免押注单一爆款。
4. 压低固定成本
比较居家、小团队、外包和逐步招聘方案，先让盈利 SKU 支撑扩张。
5. 选择适配战场
按自身供应链、语言、合规和竞争优势比较站点与细分市场，不因焦虑频繁换赛道。
6. 设置决策闸门
为离职、首批采购、第二轮补货和招聘分别设前置条件与退出线。
判断标准
- 现金模型包含个人生活跑道和企业营运资金。
- 能力评估不依赖前雇主的受保护资源。
- 每个扩张动作由盈利或已验证证据支撑。
必须交付的结果
- 运营到经营者能力差距表。
- 现金流与组合成功率模型。
- 低固定成本启动方案。
- 离职或继续准备的条件式结论。
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
1 file 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 · 75 lines · 77 tokens per session scan A b9046fb74a19
sealeap-amazon-operator-to-owner-readiness is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 1mo ago), licensed MIT. It adds 77 tokens to every session and 867 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.
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