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-feature-demand-validatorgit 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-feature-demand-validator)<a href="https://agentmods.dev/skills/zach22-1999/amazon-skills/zach-feature-demand-validator"><img src="https://agentmods.dev/badge/skills/zach22-1999/amazon-skills/zach-feature-demand-validator/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-feature-demand-validator"><img src="https://agentmods.dev/badge/skills/zach22-1999/amazon-skills/zach-feature-demand-validator.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 | $0.00071 | $0.04042 |
| Opus 5 | $0.00036 | $0.02021 |
| Sonnet 5 | $0.00014 | $0.00808 |
| Haiku 4.5 | $0.00007 | $0.00404 |
Grade A, and why
zach-feature-demand-validator 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 11d 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 — 377 lines — stays where its author put it; the contents beside it link to each section on GitHub.
前置建议
本公开版 Skill 是自包含的，不依赖任何私有工作区文件、内部参考库或品牌专属协议。
开始执行前，建议先阅读本 Skill 自带的参考材料：
references/judgment_criteria.md— 三维需求判断标准references/report_template.md— 报告结构references/csv_schema.md— 交付 CSV 结构references/review_fallback_pack.md— 无 Sorftime 时的评论证据包格式
定位
亚马逊卖家的产品开发，大多数时候不是做颠覆式创新，而是在现有供给上做微创新：
- 加一个小功能
- 补一个小结构
- 优化一个小体验
危险点也恰好在这里。很多功能看起来合理，但很可能只是卖家自己的想象，不是消费者真实在意的点。
这个 Skill 的定位，不是帮你发明新物种，而是判断：
这个微创新，到底是不是用户真的在意。
它通过三个独立维度交叉验证，避免“感觉有需求就开模”。
| 维度 | 首选数据源 | 无 Sorftime 时的替代方案 |
|---|---|---|
| Review 信号 | Sorftime product_reviews |
WebSearch + WebFetch 主动抓取 Amazon Review 页面，或用户提供 review_source_pack |
| 关键词信号 | Sorftime keyword_detail / keyword_trend / keyword_extends |
Google Trends（WebFetch）+ Amazon Autocomplete（WebSearch）+ 第三方搜索量估算 |
| 社区信号 | WebSearch（Reddit + Quora） | 继续可执行（不依赖 Sorftime） |
上游 / 下游
- 上游：
zach-product-research、zach-competitor-deep-dive - 下游：
zach-new-product-listing-writer
执行优先级
路线 A：Sorftime 完整版
适用条件：当前环境可调用 Sorftime MCP。
- Review 维度走 Sorftime
product_reviews - 关键词维度走 Sorftime 关键词工具
- 社区维度走 WebSearch
路线 B：无 Sorftime 替代版
适用条件：当前环境没有 Sorftime MCP。
- Review 维度：优先用 WebSearch + WebFetch 主动抓取 Amazon Review；若抓取失败，再降级到用户提供的
review_source_pack - 关键词维度：用 Google Trends + Amazon Autocomplete + 第三方工具获取免费搜索数据
- 社区维度：继续走 WebSearch
注意：替代版的数据精度不如 Sorftime（无法拿到精确周搜索量和 CPC），但三个维度都有真实数据支撑，不存在”空白维度”。报告中需标注数据来源差异。
输入方式
业务输入
支持两类：
| 输入方式 | 示例 | 处理逻辑 |
|---|---|---|
| 品类 + 功能描述 | air fryer + steam feature |
先找市场上是否已有带该功能的产品 |
| ASIN + 功能描述 | B0XXXX + self-cleaning |
直接围绕指定产品和相邻竞品验证 |
默认站点：US
Review fallback 输入
当 Sorftime 不可用时，用户需要提供本地评论证据包：
review_source_pack/
├── source_manifest.json
└── raw/
├── reviews.csv
├── reviews.txt
└── reviews.html
详细格式见 references/review_fallback_pack.md。
执行流程
Step 0：解析任务与构造关键词
- 确认输入是“品类 + 功能”还是“ASIN + 功能”
- 确认站点，默认
US - 基于
references/keyword_construction_guide.md构造 3-5 个英文关键词变体 - 判断当前走 Sorftime 完整版还是 Review fallback 降级版
What ships with it
17 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.
- examples/review-source-pack/raw/reviews.csv 246 B
- examples/review-source-pack/raw/reviews.txt 319 B
- examples/review-source-pack/README.md 724 B
- examples/review-source-pack/source_manifest.json 304 B
- README.md 5.9 KB
- references/csv_schema.md 4.9 KB
- references/judgment_criteria.md 5.7 KB
- references/keyword_construction_guide.md 2.7 KB
- references/report_template.md 3.8 KB
- references/review_fallback_pack.md 2.7 KB
- scripts/__init__.py 59 B runs code
- scripts/generate_community_csv.py 3.4 KB runs code
- scripts/generate_keyword_csv.py 4.6 KB runs code
- scripts/parse_review_source_pack.py 9.0 KB runs code
- scripts/parse_reviews.py 12 KB runs code
- scripts/validate_deliverables.py 9.3 KB runs code
- scripts/WINDOWS_USAGE.md 1.9 KB
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.
- 11d ago First seen · 377 lines · 71 tokens per session scan A e166fd46745a
zach-feature-demand-validator is a skill published in the GitHub repository zach22-1999/amazon-skills (187 stars, last pushed 22d ago), licensed MIT. It adds 71 tokens to every session and 4,042 once invoked, about $0.0004 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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