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Amazon Review Reveyes

Name: Amazon Review Reveyes
Author: zhuojiuya

作者 zhuojiuya · GitHub ↗ · v1.0.0 · MIT-0

cross-platform ✓ 安全检测通过

125

总下载

当前安装

版本数

在 OpenClaw 中安装

/install amazon-review-reveyes

功能描述

使用 Reveyes API 批量抓取亚马逊商品评论，支持 20 个站点。输出评论列表、星级分布统计和差评摘要。 Use when: 用户提到抓评论、查差评、分析竞品口碑、给出 ASIN 编号需要评论数据。 NOT for: 分析已经抓好的本地评论文件，或查询亚马逊商品价格/销量。

使用说明 (SKILL.md)

When to Run

用户发送 ASIN 编号并要求抓取评论（如「帮我抓 B08N5WRWNW 的评论」）
用户说「帮我看看这个竞品的差评」「分析一下这款产品的用户反馈」
用户要对比同一商品在多个亚马逊站点的口碑
用户要导出评论数据做分析

Parameters

从用户消息中提取以下信息：

参数	说明	默认值
`asin`	亚马逊 ASIN，10 位字母数字（必须）	—
`marketplace`	站点代码，见下方列表	`US`
`pages`	抓取页数（1-10），1 页约 10 条评论	`2`
`filter_star`	星级筛选：`all_stars` `positive` `critical` `five_star`…`one_star`	`all_stars`

支持的站点代码： US CA MX UK DE FR IT ES NL SE PL BE IE JP IN SG AE SA AU BR

Workflow

提取参数：从用户消息中识别 ASIN（10 位）、站点代码、页数、星级筛选
- 若用户只给 ASIN，其余使用默认值
- 若用户说「差评」自动设置 filter_star=critical
- 若用户说「好评」自动设置 filter_star=positive

执行抓取：调用 scripts/fetch.py，传入参数

python scripts/fetch.py \x3CASIN> \x3Cmarketplace> \x3Cpages> \x3Cfilter_star>

等待完成：脚本内部自动轮询（最多 5 分钟），完成后输出 JSON 结果
格式化输出：
- 汇总：总评论数、平均评分、各星级占比
- Top 5 差评（如请求的是 critical 或 all_stars）：标题 + 正文前 150 字
- 如评论数 > 20，额外输出高频关键词（从差评标题提取）
错误处理：
- AuthenticationError → 提示用户检查 REVEYES_API_KEY
- InsufficientCreditsError → 提示前往 https://www.reveyes.cn 充值
- BadParamsError → 提示检查 ASIN 或站点代码是否正确
- TimeoutError → 告知任务仍在运行，提供 task_id 供后续查询

Output Format

📦 ASIN: B08N5WRWNW  |  站点: US  |  共 87 条评论

⭐ 评分分布：
  ★★★★★  42 条 (48%)  ████████████
  ★★★★☆  18 条 (21%)  █████
  ★★★☆☆   8 条  (9%)  ██
  ★★☆☆☆   5 条  (6%)  █
  ★☆☆☆☆  14 条 (16%)  ████

📝 典型差评（最近 5 条）：
1. ★★ "Stopped working after 2 weeks"
   Bought this expecting quality but it broke down...

2. ★★ "Not as described"
   The color is completely different from the photos...

[查看完整结果或导出 CSV，请告诉我]

安全使用建议

This skill appears to do what it says: it calls the Reveyes API to fetch Amazon reviews and requires only REVEYES_API_KEY. Before installing, verify you trust Reveyes (https://www.reveyes.cn), confirm the 'reveyes' Python package on PyPI is legitimate, and be aware that using the skill will consume credits on your Reveyes account. If you have strict offline or secret-handling policies, ensure the agent environment only supplies REVEYES_API_KEY (and no other unrelated credentials). Finally, review the reveyes SDK and the referenced GitHub repo if you want to audit network behavior or data retention policies.

功能分析

Type: OpenClaw Skill Name: amazon-review-reveyes Version: 1.0.0 The skill is a legitimate integration for fetching Amazon product reviews via the Reveyes API. It utilizes a dedicated Python SDK (reveyes) and follows a transparent workflow of parameter extraction, API interaction, and data summarization. The code in scripts/fetch.py is straightforward and handles the REVEYES_API_KEY as expected for authentication, with no evidence of data exfiltration, malicious execution, or harmful prompt injection in the SKILL.md instructions.

能力评估

✓ Purpose & Capability

Name/description, README, SKILL.md, clawhub.json, and scripts/fetch.py all align: the skill calls the Reveyes API to fetch Amazon reviews. The single required env var (REVEYES_API_KEY) and the declared pip dependency on 'reveyes' are appropriate for this purpose.

✓ Instruction Scope

SKILL.md explicitly limits runtime behavior (extract parameters, call scripts/fetch.py, format results). The instructions reference only the REVEYES_API_KEY and the included script; they do not ask to read unrelated local files, other credentials, or send data to unexpected endpoints.

ℹ Install Mechanism

This is an instruction-only skill with a bundled helper script (no install spec). clawhub.json declares a pip requirement ('reveyes>=0.1.2') and README instructs running 'pip install reveyes'. No arbitrary URL downloads or archive extraction are present, but the user should be aware that the reveyes Python package will need to be installed from PyPI.

✓ Credentials

Only REVEYES_API_KEY is required and it is justified by the stated integration. No unrelated secrets or system config paths are requested.

✓ Persistence & Privilege

always is false and there is no indication the skill modifies other skills or system-wide agent settings. It behaves as a normal, user-invokable skill.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install amazon-review-reveyes
安装完成后，直接呼叫该 Skill 的名称或使用 /amazon-review-reveyes 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.0

Rename to amazon-review-reveyes for better discoverability

元数据

Slug amazon-review-reveyes

版本 1.0.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

常见问题