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-scalable-portfolio-six-lanesgit 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-scalable-portfolio-six-lanes)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-scalable-portfolio-six-lanes"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-scalable-portfolio-six-lanes/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-scalable-portfolio-six-lanes"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-scalable-portfolio-six-lanes.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 | $0.00063 | $0.01151 |
| Opus 5.5 | $0.00025 | $0.00460 |
| Sonnet 5.5 | $0.00013 | $0.00230 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
sealeap-xiezhi-amazon-scalable-portfolio-six-lanes 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 可复制组合六赛道
目标
按团队能力把候选分入六种结构性机会赛道，每种赛道使用独立证据和风险门槛。
适用任务
- 建立多赛道选品雷达。
- 选择与供应链和团队能力匹配的方向。
- 避免把低评论或多 SKU 简化为铺货。
开始前要拿到
- 团队资金、供应链、认证、物流、海外仓和设计能力。
- 各赛道的需求、竞品、评论、价格和关键词证据。
- 当前可接受的库存、退货和合规风险。
- 多 SKU 管理、素材和广告容量。
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。
- 不得把政策、认证、物流困难视为可以规避的竞争壁垒。
- 所有变体、评论和流量策略必须保持合规。
工作流
1. 冷门细分
寻找精准需求、竞品较少且低评论正常出单的中小市场。
2. 可扩变体
选择真实可按图案、颜色、规格或主题扩展且符合 variation policy 的产品。
3. 大件高货值
只有具备物流、配送、退货翻新和现金能力时，才评估天然高门槛大件。
4. 高门槛产品
仅在认证、开发、质量体系和授权已具备时评估，不把监管复杂性当作轻易红利。
5. 季节与活动
用历史周期和提前布局寻找阶段需求，并以保守库存管理季末风险。
6. 高客单与套装
通过真实价值、便利和单位经济提升客单，不以虚假组合制造价格。
7. 组合配置
对每条赛道计算能力匹配、风险、资本占用和预期贡献，设年度配置上限。
判断标准
- 六赛道是机会分类，不是每个团队都应覆盖全部。
- 低评论正常出单是共同线索，但必须结合精准词、单位经济和异常排除。
- 高认证和大件产品的损失尾部更大，缺少能力时直接 NO-GO。
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
- 六赛道能力矩阵
- 候选路由清单
- 资本/风险配置
- 每赛道验证门槛
- 季度产品管线
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 · 94 lines · 63 tokens per session scan A 843f3ac8665f
sealeap-xiezhi-amazon-scalable-portfolio-six-lanes is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 1,151 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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