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 zach22-1999/amazon-skills --skill zach-search-term-analyzergit clone --depth 1 https://github.com/zach22-1999/amazon-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/zach22-1999/amazon-skills/zach-search-term-analyzer)<a href="https://agentmods.dev/skills/zach22-1999/amazon-skills/zach-search-term-analyzer"><img src="https://agentmods.dev/badge/skills/zach22-1999/amazon-skills/zach-search-term-analyzer/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/zach22-1999/amazon-skills/zach-search-term-analyzer"><img src="https://agentmods.dev/badge/skills/zach22-1999/amazon-skills/zach-search-term-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00133 | $0.03185 |
| Opus 5 | $0.00067 | $0.01592 |
| Sonnet 5 | $0.00027 | $0.00637 |
| Haiku 4.5 | $0.00013 | $0.00318 |
Grade A, and why
zach-search-term-analyzer 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon Brand Analytics 搜索词分析（v3 场景化框架）
分析 Brand Analytics Top Search Terms（热门搜索词）报告（任何类目），按"自家 ASIN 在/不在点击 TOP3"做场景路由，输出市场结构判断与实操建议。
数据来源（⚠️ 重要区分）
本工具分析的是 Brand Analytics → Top Search Terms（热门搜索词） 报告，不是 PPC 搜索词报告；如果文件字段不包含下方必需字段，先停下确认报告类型。
| Brand Analytics Top Search Terms | PPC 搜索词报告 | |
|---|---|---|
| 来源 | Seller Central → Brand Analytics | 广告后台 → SP/SB Campaign |
| 数据范围 | 全平台搜索词（与你的产品无关也能查） | 仅与你的广告触发相关的搜索词 |
| 核心指标 | 搜索频率排名、点击份额、转化份额 | Impressions、Clicks、Spend、Sales、ACOS |
| 适用场景 | 市场分析、选品定位、Listing 关键词策略、自家词份额监控 | 广告优化、出价调整、否定词管理 |
⚠️ 使用 Brand Analytics 需要完成品牌备案（Brand Registry）。PPC 搜索词报告请用
zach-search-term-report-analyzer。
报告口径速查（判读前必读）
| 口径 | 内容 |
|---|---|
| Search Frequency Rank | 全平台相对排名不是搜索量；#1 与 #2 可差数量级；跨类目/跨站点不可比 |
| TOP3 商品 | 该词下被点击最多的 3 个 ASIN（含广告位点击）——是"点击王"不是"转化王"，转化最高的 ASIN 可能不在表里 |
| 点击份额 / 转化份额 | 独立指标：买家可点 A 买 B，所以 TOP3 转化份额为 0/缺失是常见真实现象（转化分散到长尾或被脱敏），不是数据错误 |
| 成交系数 | 转化份额 ÷ 点击份额 = 该 ASIN 转化率 ÷ 该词平均转化率；≥1 = Closer，<1 = 流量磁铁 |
| 粒度与滞后 | 日/周/月/季可选，实战以周报为主；数据滞后约 T+3~T+7；低频词被脱敏不显示 |
| 定位边界 | ABA 代表热度流量，不必然代表市场需求全貌 |
数据诚信规则（⭐ 最高优先级）
- 绝不捏造数据：所有分析数据来自用户提供的报告原始文件，没有数据就说"暂无"
- 缺失≠零：转化份额缺失/全 0 的词单列 B0"数据不足"，不参与象限判定，不得判为"转化差"
- 区分事实与推断：数据结论标「📊 数据事实」，策略建议标「💡 分析推断」
- 排名≠搜索量：搜索频率排名只表示相对位置
- 时效性：建议用最近 3-6 个月数据；强季节性产品参考上个旺季同期，且不同时段分开分析
场景框架（v3 核心）
场景路由
自家 ASIN ∈ 该词点击 TOP3 ？
├─ 是 → 场景 A：存量经营（看自家行 + 同词竞品行）
├─ 否 → 场景 B：市场进入（看 TOP3 合计的市场结构）
└─ 未提供自家 ASIN → 全部场景 B，报告显著标注"仅市场视角"
场景 A：自家在 TOP3（防守/收割视角）
| 状态 | 判定（默认阈值） | 动作 |
|---|---|---|
| A1 收割词 | 自家成交系数 ≥ 1.0 | 防守+放量：加预算、防御性投放、盯竞品进入 |
| A2 漏水词 | 自家点击份额 − 转化份额 > 4pt | 先修详情页再抬价：价格/评价/主图/A+，用 SQP 定位漏斗卡点 |
| A4 份额预警 | 曾在 TOP3、最新一期掉出（或点击份额连续下滑） | 排查排名/价格/断货/新竞品 |
| A5 平衡词 | 介于两者之间 | 维持现状，周度跟踪 |
附加信号：同词 TOP3 内竞品成交系数 <1 → 截流机会（SP/SD 定向+压价）。
场景 B：自家不在 TOP3（进攻/进入视角）
两轴：点击集中度 = SUM(TOP3 点击份额)；头部满足度 = SUM(转化份额) ÷ SUM(点击份额)：
| 象限 | 判定（默认阈值） | 结构解读 | 动作 |
|---|---|---|---|
| B1 机会词 | 集中度 <50% 且 满足度 <1.0 | 点击分散且头部接不住需求，转化流向 TOP3 之外 | 优先级最高：产品能接住意图则优先投放+进 Listing；先核对 TOP3 属性一致性 |
| B2 常规竞争词 | 集中度 <50% 且 满足度 ≥1.0 | 蛋糕未整合、头部转化健康 | 可进：常规差异化+正常出价测试 |
| B3 头部满足词 | 集中度 ≥50% 且 满足度 ≥1.0 | 头部垄断且高效满足市场 | 避其锋芒：不正面竞价，找相邻长尾切入 |
| B4 伏击词 | 集中度 ≥50% 且 满足度 <1.0 | 头部霸点击但买家买了别家 | 伏击：竞品定向+压价，用转化力偷单，不打点击战 |
| B0 数据不足 | 转化数据缺失/分散/脱敏 | 无法判定头部满足度 | 不判定；转 SQP/广告数据验证 |
What ships with it
6 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.
- 12d ago First seen · 172 lines · 133 tokens per session scan A e3d9c3b72c51
zach-search-term-analyzer is a skill published in the GitHub repository zach22-1999/amazon-skills (188 stars, last pushed 22d ago), licensed MIT. It adds 133 tokens to every session and 3,185 once invoked, about $0.0007 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 2026-08-30.
Other skills, from other repositories
ecom-applicability
Determine whether AI is appropriate for a specific e-commerce task. Use when evaluating if a problem has enough data, the right tools, or acceptable risk for AI automation. Answers 'should I use AI for X?' with boundary-aware reasoning.
ecom-social
Instructions for creating and improving e-commerce social-media content, advertising, and community work across platforms such as Instagram, YouTube, TikTok, Pinterest, Reddit, WhatsApp, and Xiaohongshu.
ecom-advertising
Diagnose and optimize Amazon PPC campaigns. Use for ACOS analysis, bid optimization, keyword harvesting, campaign structure, or multi-marketplace advertising.
ecom-compliance
Check product compliance, HS codes, IP risks, and platform requirements. Use for category approval, FDA/FCC/CE documentation, IP infringement screening, or dangerous goods classification.
ecom-customer-service
Respond to buyer messages and negative reviews, draft refund and return replies, review-request emails, Plan of Action appeals, FAQ, and CS KPI tracking. Use for complaint handling, account appeal, or after-sales support.
ecom-inventory
Forecast inventory, set safety stock, and manage replenishment. Use for FBA inventory planning, demand forecasting, restock decisions, or multi-warehouse optimization.