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-factory-capability-market-matchinggit 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-factory-capability-market-matching)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-factory-capability-market-matching"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-factory-capability-market-matching/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-factory-capability-market-matching"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-factory-capability-market-matching.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 | $0.00056 | $0.01150 |
| Opus 5.5 | $0.00022 | $0.00460 |
| Sonnet 5.5 | $0.00011 | $0.00230 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
sealeap-xiezhi-amazon-factory-capability-market-matching 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 工厂能力与市场匹配
目标
不把供应链优势误当市场优势，而将材料与工艺能力组合到具体人群、场景和任务中寻找可经营需求。
适用任务
- 为工贸一体卖家寻找细分市场。
- 把材料或工艺通用词映射到多个用途。
- 比较原大通货赛道与新场景赛道。
开始前要拿到
- 工厂材料、设备、工艺、尺寸、产能、MOQ、认证和质量边界。
- 原有产品及客户用途。
- 材料/工艺词与场景/人群/节日词组合。
- 候选市场的商品、价格、评论、销量、CPC 与合规要求。
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。
- 不得用工厂客户销量、品牌或知识产权作为自身可复制资产。
- 不得绕过认证、安全、标签或分销授权要求。
工作流
1. 制作能力护照
把工厂优势写成可验证的材料、工艺、成本、速度、质量和 MOQ，而不是笼统的供应链好。
2. 生成通用词
从材料、工艺、产品结构和生产流程提取当地市场常用表达。
3. 组合需求词
将能力词分别与人群、空间、活动、节日和使用任务组合，跨类目发现商品。
4. 筛低门槛样本
优先研究低评论正常出单、有精准词、价格可覆盖广告且工厂无需大改的方向。
5. 比较新旧赛道
对竞争、CPC、MOQ、开发、认证、物流和利润逐项比较，避免只看生产成本。
6. 验证可交付
做样品、质量标准、包装、标签和小批量交期核查后，才进入商业验证。
判断标准
- 供应链优势解决能否生产，市场优势解决消费者为何选择；两者必须同时成立。
- 材料/工艺 + 场景/人群/节日是发现公式，不是需求证明。
- 高门槛产品只有在工厂真实具备认证和质量体系时才是优势。
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
- 工厂能力护照
- 通用词组合矩阵
- 候选细分市场
- 新旧赛道经济对比
- 样品与小批验证计划
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 · 56 tokens per session scan A ef237843441e
sealeap-xiezhi-amazon-factory-capability-market-matching is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 1,150 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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