Agent skill

Sealeap Xiezhi Amazon Low Review New Entrant Validation

by xjli360 in xjli360/sealeap-amazon-skills

Validate whether an Amazon niche with dominant old listings still admits low-review new entrants.

MITAuto-check passed

Install Sealeap Xiezhi Amazon Low Review New Entrant Validation

skills CLI
$ npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-low-review-new-entrant-validation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install xjli360/sealeap-amazon-skills sealeap-xiezhi-amazon-low-review-new-entrant-validation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/xjli360/sealeap-amazon-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-low-review-new-entrant-validation .claude/skills/sealeap-xiezhi-amazon-low-review-new-entrant-validation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
sealeap-xiezhi-amazon-low-review-new-entrant-validation
GitHub stars
251
Token cost
~499 tokens
SKILL.md length
91 words
Files
5 (incl. scripts, references)
Skills in repo
179
Repo updated
First seen
Licence
MIT

At a glance

Validate whether an Amazon niche with dominant old listings still admits low-review new entrants.

  • Works in 5 steps: 建立时间队列 → 寻找正常赢家 → 解释购买理由 → …
  • The first search page looks saturated but the user wants to test for unmet audience
  • SKILL.md covers 目标, 适用任务, 开始前要拿到 and 不可妥协的边界, plus 4 more sections
  • Runs Python scripts from its folder

What it does

Sealeap Xiezhi Amazon Low Review New Entrant Validation is an agent skill from xjli360/sealeap-amazon-skills. Validate whether an Amazon niche with dominant old listings still admits low-review new entrants. Use when the first search page looks saturated but the user wants to test for unmet audience, scenario, form, size, or price-segment demand.

Its SKILL.md is about 500 tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/mcp-data-plan.md` and `references/playbook.md`).

It works with Model Context Protocol. The repository describes itself as: Reusable Agent Skills for Amazon product research, listings, advertising, inventory, and operations. The licence is MIT.

When your agent uses it

  • The first search page looks saturated but the user wants to test for unmet audience
  • Price-segment demand

Example prompts

  • “/sealeap-xiezhi-amazon-low-review-new-entrant-validation”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. 建立时间队列
  2. 寻找正常赢家
  3. 解释购买理由
  4. 量化友好度
  5. 验证可见性

What it can do on your machine

Read from SKILL.md and the folder at commit 497d4b8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Sealeap Xiezhi Amazon Low Review New Entrant Validation loads about 499 tokens when it runs, and up to ~2.7k if it reads all its reference files. Until then it costs about 74 tokens; SKILL.md has 91 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~74
When it runs · the whole SKILL.md, loaded when a task matches
~499
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from xjli360/sealeap-amazon-skills at commit 497d4b8, republished under its MIT licence (© xjli360). 91 words, ~499 tokens.

Download SKILL.mdSave it as .claude/skills/sealeap-xiezhi-amazon-low-review-new-entrant-validation/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
sealeap-xiezhi-amazon-low-review-new-entrant-validation
description
Validate whether an Amazon niche with dominant old listings still admits low-review new entrants. Use when the first search page looks saturated but the user wants to test for unmet audience, scenario, form, size, or price-segment demand.

Amazon 低评论新品机会验证

目标

不以首页老链接数量下结论,而通过近期低评论新品的正常增长和明确购买理由判断市场是否仍有入口。

适用任务

  • 判断红海搜索页是否仍有新品机会。
  • 解释近期新品为何出单。
  • 区分真实需求创新与异常运营样本。

开始前要拿到

  • 通用词与更精确的属性/场景词。
  • 近 30 天、3 个月和 6 个月新品样本。
  • 评论、销量、价格、关键词排名、广告与变体信号。
  • 头部与低评论竞品的同口径销量。

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。
  • 不得将合并评论、异常评价或站外强推当作可复制能力。
  • 差异化必须合法、可感知并有需求证据。

工作流

1. 建立时间队列

按上架时间和评论层级形成新品队列,避免只观察多年老链接。

2. 寻找正常赢家

识别低评论但稳定出单、流量词与卖点一致、无明显异常增长的新品。

3. 解释购买理由

归因到可见的结构、尺寸、场景、对象、造型、组合或价格带差异,而不是只记录销量。

4. 量化友好度

比较低评论样本与头部样本的同口径销量或转化代理值,并同时报告样本量和分布。

5. 验证可见性

确认差异在搜索页主图、标题和价格区间即可被消费者理解,否则不把它视为有效入口。

判断标准

  • 低评论组销量/头部组销量超过约 15%或20%可作为友好信号之一,不是官方标准。
  • 单个新品异常爆量不能代表市场开放;需要一组可解释样本。
  • 没有明显购买理由、关键词对不上或流量异常的样本应剔除。

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

  • 新品队列
  • 正常/异常样本分类
  • 购买理由矩阵
  • 市场友好度区间
  • 进入、观察或放弃结论

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。

© xjli360, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-low-review-new-entrant-validation of xjli360/sealeap-amazon-skills.

  • SKILL.md
  • agents/openai.yaml
  • references/mcp-data-plan.md
  • references/playbook.md
  • scripts/mcp_research.py

Open the folder on GitHubat commit 497d4b8

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Questions about Sealeap Xiezhi Amazon Low Review New Entrant Validation

What does Sealeap Xiezhi Amazon Low Review New Entrant Validation do?

Validate whether an Amazon niche with dominant old listings still admits low-review new entrants. Sealeap Xiezhi Amazon Low Review New Entrant Validation is an agent skill from xjli360/sealeap-amazon-skills. Validate whether an Amazon niche with dominant old listings still admits low-review new entrants.

When should I use Sealeap Xiezhi Amazon Low Review New Entrant Validation?

Sealeap Xiezhi Amazon Low Review New Entrant Validation fits situations like: the first search page looks saturated but the user wants to test for unmet audience; price-segment demand.

How do I install Sealeap Xiezhi Amazon Low Review New Entrant Validation in Claude Code?

Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-low-review-new-entrant-validation -a claude-code`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-low-review-new-entrant-validation in xjli360/sealeap-amazon-skills) into .claude/skills/sealeap-xiezhi-amazon-low-review-new-entrant-validation in your project. Claude Code loads it when a task matches its description.

How do I install Sealeap Xiezhi Amazon Low Review New Entrant Validation in Codex?

Run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-low-review-new-entrant-validation -a codex`. Or copy the skill folder (amazon-skills/douyin/xiezhi/sealeap-xiezhi-amazon-low-review-new-entrant-validation in xjli360/sealeap-amazon-skills) into .agents/skills/sealeap-xiezhi-amazon-low-review-new-entrant-validation in your project. Codex loads it when a task matches its description.

Can I use Sealeap Xiezhi Amazon Low Review New Entrant Validation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add xjli360/sealeap-amazon-skills --skill sealeap-xiezhi-amazon-low-review-new-entrant-validation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sealeap-xiezhi-amazon-low-review-new-entrant-validation, .gemini/skills/sealeap-xiezhi-amazon-low-review-new-entrant-validation, .github/skills/sealeap-xiezhi-amazon-low-review-new-entrant-validation and .opencode/skills/sealeap-xiezhi-amazon-low-review-new-entrant-validation in your project.

What does Sealeap Xiezhi Amazon Low Review New Entrant Validation need to run?

Going by SKILL.md and its folder, Sealeap Xiezhi Amazon Low Review New Entrant Validation needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Sealeap Xiezhi Amazon Low Review New Entrant Validation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Sealeap Xiezhi Amazon Low Review New Entrant Validation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Sealeap Xiezhi Amazon Low Review New Entrant Validation use?

Sealeap Xiezhi Amazon Low Review New Entrant Validation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sealeap Xiezhi Amazon Low Review New Entrant Validation use?

About 499 tokens (SKILL.md is roughly 2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.2k tokens, read only when the agent opens those files.

What are the alternatives to Sealeap Xiezhi Amazon Low Review New Entrant Validation?

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Who maintains Sealeap Xiezhi Amazon Low Review New Entrant Validation?

xjli360 (a GitHub user) maintains it in xjli360/sealeap-amazon-skills, which has 251 GitHub stars. The repository holds 179 skills in this directory. The repository was last updated on September 28, 2026.

Source: xjli360/sealeap-amazon-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.