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zach-product-research

zach-product-research is a skill for Claude Code from zach22-1999/amazon-skills. It costs 89 tokens per session (20,410 once invoked), scanned A, original, MIT.

A Sorftime-based product research skill for finding Amazon market opportunities and deciding whether a new product is worth pursuing. Sorftime is a market-research data source for Amazon sellers.

In plain words
What is it for?
Researching products before launch, analyzing competition and market structure, estimating profitability and investment, and producing reports in Markdown, HTML, dashboard, spreadsheet, and JSON formats.
Why use it?
It brings market demand, product attributes, competition, costs, returns, and entry barriers into one Go/No-Go decision instead of relying on a single metric.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

not rated 188repo +13 23d ago A scan SkillSpector: pass 89 tokens original MIT

Good fit Researching products before launch, analyzing competition and market structure, estimating profitability and investment, and producing reports in Markdown, HTML, dashboard, spreadsheet, and JSON formats.

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Install with agentmods
npx agentmods add skills/zach22-1999/amazon-skills/zach-product-research
View source ↗ zach22-1999/amazon-skills
Install

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.

Any agent
npx skills add zach22-1999/amazon-skills --skill zach-product-research
Clone the repo
git clone --depth 1 https://github.com/zach22-1999/amazon-skills

Made for: Claude Code.

Wrote 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.

agentmods badge for zach-product-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/zach22-1999/amazon-skills/zach-product-research/github.svg)](https://agentmods.dev/skills/zach22-1999/amazon-skills/zach-product-research)
Your own site
<a href="https://agentmods.dev/skills/zach22-1999/amazon-skills/zach-product-research"><img src="https://agentmods.dev/badge/skills/zach22-1999/amazon-skills/zach-product-research/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.

agentmods 80×15 button for zach-product-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/zach22-1999/amazon-skills/zach-product-research"><img src="https://agentmods.dev/badge/skills/zach22-1999/amazon-skills/zach-product-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 89 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 20,410 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00089 $0.20410
Opus 5 $0.00044 $0.10205
Sonnet 5 $0.00018 $0.04082
Haiku 4.5 $0.00009 $0.02041

Measured 13d ago against content hash 5221ae487732, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

zach-product-research 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 13d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/__init__.py, scripts/cross_analysis.py, scripts/parse_top100_dimensions.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/zach-product-research/SKILL.md · 1,272 lines

How it starts

The opening of the file, as written. The whole thing — 1,272 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。

开始分析前，优先阅读本 Skill 自带的参考材料：

  • references/payload_schema_v2.md — v2 数据包结构与必填字段
  • references/payload_schema.md — v1 兼容格式
  • references/html_report_spec.md — HTML 精简报告结构要求
  • references/analysis_patterns.md — 分析模式与洞察写法模板

如果你已有自己的市场研究资料，可以作为补充背景使用；但本 Skill 的执行、交付和校验不依赖外部私有资料。

选品分析器（Product Research - Sorftime MCP）

定位

基于 Sorftime MCP 的选品分析，帮助你在有利润前提下，用最短时间、最低风险发现高潜力市场机会。

数据来源：全部通过 Sorftime MCP 工具获取，不捏造、不估算。

下游输出：选品报告（MD + HTML精简 + Dashboard看板 + Excel）→ 新品上架工作流的后续步骤：zach-competitor-deep-dive（Listing 级竞品拆解）→ zach-pricing-strategy（定价精算）→ …

注：本 Skill 已吸收原 zach-market-intelligence 的 Go/No-Go 决策框架与进入壁垒评估能力（见 Step 2.4 / Step 3.5），以及 zach-report-dashboard-renderer 的 Dashboard 可视化看板能力。两者均已标记为 deprecated。

Script Directory

  • scripts/render_deliverables.py
    • 用途：把统一 JSON 数据包渲染为 md + html精简 + dashboard看板 + xlsx + json，并执行交付校验
    • v2 模式（推荐）：payload 含 schema_version: “2.0” + chapters，渲染器从结构化数据生成表格 + 插入 LLM 洞察段落
    • v1 兼容模式：payload 含 report_markdown / report_html，直接写入（旧流程）
    • 命令：
      • python skills/zach-product-research/scripts/render_deliverables.py generate --input <payload.json>
      • python skills/zach-product-research/scripts/render_deliverables.py validate --input <payload.json>
      • python skills/zach-product-research/scripts/render_deliverables.py all --input <payload.json>
    • 适用时机：Step 5 交付阶段，禁止手工只补单个文件后直接结束任务
  • scripts/parse_top100_dimensions.py
    • 用途：按规则文件解析 Top100 标题维度，输出 top100_parsed.json 与 uncertain_products.json
  • scripts/cross_analysis.py
    • 用途：基于解析后的产品 JSON 生成交叉矩阵和机会空白点

References

  • references/payload_schema_v2.md
    • 用途：v2 payload 结构定义（10 章 chapters + excel_sheets），准备 render_deliverables.py 输入数据包时查看
  • references/payload_schema.md
    • 用途：v1 payload 结构定义（向后兼容参考）
  • references/html_report_spec.md
    • 用途：HTML 精简报告区块定义参考
  • references/analysis_patterns.md
    • 用途：四种分析模式的模板与示例，报告写作时必须引用（至少使用 3 种）

Assets

  • assets/html_report_template.html
    • 用途：HTML 精简报告模板（v1 使用，v2 由 render_deliverables.py 内置渲染）
  • assets/dashboard_template.html
    • 用途：Dashboard 可视化看板模板（从 zach-report-dashboard-renderer 迁入），v2 由 render_deliverables.py 自动注入数据

Read the full file on GitHub · 1,272 lines

Files

What ships with it

18 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.

Changes

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.

  1. 13d ago First seen · 1,272 lines · 89 tokens per session scan A 5221ae487732

Subscribe to this mod's changes

zach-product-research is a skill published in the GitHub repository zach22-1999/amazon-skills (188 stars, last pushed 23d ago), licensed MIT. It adds 89 tokens to every session and 20,410 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.

Claude CodeE-commerceResearchagent-skillsamazon-fbaamazon-ppcamazon-sellercodex
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