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-red-ocean-micro-niche-discoverygit 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-red-ocean-micro-niche-discovery)<a href="https://agentmods.dev/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-red-ocean-micro-niche-discovery"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-red-ocean-micro-niche-discovery/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-red-ocean-micro-niche-discovery"><img src="https://agentmods.dev/badge/skills/xjli360/sealeap-amazon-ad-skills/sealeap-xiezhi-amazon-red-ocean-micro-niche-discovery.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 | $0.00059 | $0.01170 |
| Opus 5 | $0.00030 | $0.00585 |
| Sonnet 5 | $0.00012 | $0.00234 |
| Haiku 4.5 | $0.00006 | $0.00117 |
Grade A, and why
sealeap-xiezhi-amazon-red-ocean-micro-niche-discovery 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.
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 红海微细分发现
目标
从红海类目中定位近期正常做起的低评论差异样本，提取其精准属性，再发现未被充分覆盖的相邻微细分。
适用任务
- 在指定红海类目内找蓝海细分。
- 从近期低评论赢家提取属性词。
- 把一个元素扩展成合法且可见的新设计方向。
开始前要拿到
- 目标类目与产品通用词。
- 近期上架、低评论商品及其销量、评价、变体和广告信号。
- 自然关键词、标题词频和搜索结果。
- 设计能力、IP 筛查、成本和流量经济。
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。
- 不得复制竞品图案、外观或品牌表达。
- 不得把异常运营样本包装为正常市场机会。
工作流
1. 锁定全类目
提取类目通用词并按预定样本上限、分页与筛选条件检索相关商品，记录覆盖范围和遗漏；不能把可见样本宣称为全量市场，也不以单个热门关键词代表类目。
2. 筛近期低评论
按上架时间和评论层级找有正常销量的样本，同时排除合并、异常评价、站外强推和极端促销。
3. 提取精准属性
从自然排名、标题与搜索结果识别图案、结构、材质、尺寸、对象或场景属性。
4. 比较评论层级
确认该属性词下低评论与成熟链接的销量差距不过度悬殊，并检查多个样本。
5. 扩展相邻元素
在相同消费者审美或任务下提出不同但合法的元素/设计方向，重新验证需求与竞品。
6. 完成商业闸门
核算 CPC/CVR、单位经济、供应链、IP、安全和首批库存后再决策。
判断标准
- 近期低评论正常出单是需求变化线索，不是直接抄款依据。
- 属性词精准性必须由搜索结果和购买任务验证，不能只看标题词频。
- 元素迁移需要独立需求证据，并先排查版权、商标和外观风险。
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
- 红海类目基线
- 近期低评论样本池
- 精准属性词证据
- 相邻微细分地图
- 商业与合规决策
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.
- 5d ago First seen · 90 lines · 59 tokens per session scan A 8820d11f2151
sealeap-xiezhi-amazon-red-ocean-micro-niche-discovery is a skill published in the GitHub repository xjli360/sealeap-amazon-ad-skills (86 stars, last pushed 6d ago), licensed MIT. It adds 59 tokens to every session and 1,170 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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