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-report-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-report-analyzer)<a href="https://agentmods.dev/skills/zach22-1999/amazon-skills/zach-search-term-report-analyzer"><img src="https://agentmods.dev/badge/skills/zach22-1999/amazon-skills/zach-search-term-report-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-report-analyzer"><img src="https://agentmods.dev/badge/skills/zach22-1999/amazon-skills/zach-search-term-report-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 | $0.00149 | $0.02009 |
| Opus 5 | $0.00075 | $0.01005 |
| Sonnet 5 | $0.00030 | $0.00402 |
| Haiku 4.5 | $0.00015 | $0.00201 |
Grade A, and why
zach-search-term-report-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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon 搜索词报告分析（v2）
工作方式
v2 将确定性计算与语义判断分开：
搜索词报告
→ Stage A：清洗、7/14/30 天聚合、词根聚类、硬标签
→ Stage B：AI 助手或人工完成词根语义分类
→ Stage C：严格校验、词根决策继承、六类结果渲染
词根继承用于处理低样本长尾词：当单个搜索词样本不足、但所属词根样本足够时，该词继承词根级判断；词与词根样本都不足时进入低量长尾池 pool，汇总监控但不伪装成待判定。
需要的输入
| 参数 | 必须 | 默认值 | 说明 |
|---|---|---|---|
| 搜索词报告 | 是 | — | CSV / XLSX / XLSM / XLS |
| ASIN | 是 | — | 一次只分析一个 ASIN |
| 品牌 | 是 | — | 用于品牌词硬标签与输出命名 |
| 目标 ACOS | 是 | — | 使用小数，例如 0.20 |
| 站点 | 否 | US | 用于可选的 Listing 上下文抓取 |
| 报告类型 | 否 | 自动识别 | SP / SB / SD |
| 时间窗 | 否 | 7,14,30 | 用逗号分隔 |
| Listing 上下文 | 否 | 空 | 可传入本地 Markdown / 文本快照 |
如果报告包含多个 ASIN，先从清洗元数据中列出候选，再让用户选定一个；不要混合分析。目标 ACOS、品牌或 ASIN 缺失时必须补齐，不能用隐藏默认值代替。
本地参考
references/architecture.md— v2 管线、数据契约与决策顺序references/field_mapping.md— SP / SB / SD 字段映射references/decision_rules.md— 决策规则的运营解释references/term_classification.md— Stage B 分类枚举与 JSON schemareferences/output_template.md— 六类输出与完成信号scripts/prepare_search_term_analysis.py— Stage Ascripts/finalize_search_term_report.py— Stage Cscripts/clean_search_term_report.py— 清洗底层scripts/fetch_listing_context.py— 可选 Listing 上下文抓取
Stage A：准备分析工作簿
python3 skills/zach-search-term-report-analyzer/scripts/prepare_search_term_analysis.py \
<input_file> \
--asin B0XXXXXXXX \
--brand ExampleBrand \
--site US \
--target-acos 0.20 \
--windows 7,14,30 \
--listing-context-file <optional-listing-context.md> \
--output-dir outputs/search-term-report-analyzer/ExampleBrand/intermediate/
--listing-context-file 与 --report-type 均为可选参数，不使用时删除对应命令行。
Stage A 只做可复现计算：
- 标准化字段、搜索词和数值格式
- 识别无法解析的非空数值，禁止静默清零
- 按 7/14/30 天窗口聚合并重新计算 CTR、CVR、ACOS、ROAS
- 聚类搜索词词根
- 标记确定性的
asin_term与brand_term
它会在中间目录生成：
workbook.json：term、root、窗口指标和分类请求roots_for_review.md：按花费排序的待分类词根表
Stage B：完成词根分类
读取 roots_for_review.md、workbook.json 中的 Listing 上下文和 references/term_classification.md，为 classification_request.roots_to_classify 中每一个词根填写：
What ships with it
30 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.
- assets/console_template.html 31 KB
- assets/report_template.html 24 KB
- examples/listing-context-sample.md 439 B
- examples/root-classifications-sample.json 973 B
- examples/search-term-report-sample.csv 1.1 KB
- README.md 5.1 KB
- references/architecture.md 19 KB
- references/decision_rules.md 10 KB
- references/field_mapping.md 4.0 KB
- references/output_template.md 5.6 KB
- references/term_classification.md 7.3 KB
- requirements.txt 47 B
- scripts/analyze_search_term_decisions.py 43 KB runs code
- scripts/browser_utils.py 3.7 KB runs code
- scripts/clean_search_term_report.py 13 KB runs code
- scripts/fetch_listing_context.py 7.0 KB runs code
- scripts/finalize_search_term_report.py 50 KB runs code
- scripts/prepare_search_term_analysis.py 32 KB runs code
- tests/fixtures/finalize_classifications_no_orders.json 305 B
- tests/fixtures/finalize_classifications.json 2.1 KB
- tests/fixtures/finalize_stub_template.html 532 B
- tests/fixtures/finalize_workbook_no_orders.json 4.4 KB
- tests/fixtures/finalize_workbook.json 47 KB
- tests/fixtures/prepare_no_orders.csv 332 B
- tests/fixtures/prepare_small_report.csv 1.4 KB
- tests/fixtures/sample_payload.json 56 KB
- tests/test_decision_logic.py 5.7 KB runs code
- tests/test_decisions.py 27 KB runs code
- tests/test_listing_context_fetch.py 2.3 KB runs code
- tests/test_prepare.py 19 KB runs code
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 · 168 lines · 149 tokens per session scan A e127e699e157
zach-search-term-report-analyzer is a skill published in the GitHub repository zach22-1999/amazon-skills (188 stars, last pushed 23d ago), licensed MIT. It adds 149 tokens to every session and 2,009 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.
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