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review-buying-advisor审查购买顾问

Agent Skill

review-buying-advisor 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

6,610

周安装

270

GitHub Stars

公开资料未说明

下载量

2,117
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:review-buying-advisor(审查购买顾问)
来源仓库:https://github.com/harrylabsj/review-buying-advisor
安装命令:
openclaw skills install review-buying-advisor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install review-buying-advisor

简介

通过定位预期列表、阅读可访问的公共用户评论以及将证据转化为产品名称和平台来分析产品。

SKILL.md

name
review-buying-advisor
description
Analyze a product from a product name plus platform by locating the intended listing, reading public user reviews when accessible, and turning the evidence into a practical buying recommendation. Use when the user asks whether a product is worth buying on Tmall, Taobao, JD.com, Pinduoduo, Amazon, Best Buy, or similar platforms; asks for help reading reviews; wants a real user-feedback summary; wants recurring complaints, hidden risks, pros and cons, buying advice, who the product is suitable for, or how to avoid buying mistakes before ordering. Especially relevant for requests like "值不值得买", "帮我看评论", "看看口碑", "有什么坑", "适不适合买", or "帮我避坑".

Review Buying Advisor

Turn platform review evidence into a practical buying recommendation.

Use this skill when the input is a product name plus platform and the user wants help deciding whether to buy.

This skill operates in two modes:

  • Mode 1: Review-accessible mode — the platform exposes enough public review content to support analysis.
  • Mode 2: Review-limited mode — the platform blocks, weakens, or hides review content, so only a limited or inconclusive answer is possible.

Read these references as needed:

  • references/product-identification.md when the product or variant is unclear
  • references/review-sampling.md before collecting review evidence
  • references/review-signals.md when judging strengths, risks, and buyer fit
  • references/platform-notes.md when platform review quality may affect interpretation
  • references/category-playbooks.md when category-specific priorities matter
  • references/failure-modes.md when evidence is sparse, mixed, or inaccessible
  • references/output-patterns.md when preparing the final answer
  • references/examples.md when examples would help calibrate tone or structure

Workflow

  1. Identify the product.

- Accept a product name plus platform. - Match the likely listing by brand, model, category, and variant cues. - If the product is ambiguous, ask one short clarifying question. - Do not guess across multiple plausible products or variants.

  1. Check review accessibility.

- Try to access public review content on the specified platform. - Decide which mode applies: - Mode 1 if enough public review content is accessible. - Mode 2 if review content is blocked, too weak, or too incomplete.

  1. If Mode 1, analyze review evidence.

- Use a representative sample rather than only the first visible comments. - Include positive, negative, mixed, and recent reviews when possible. - Prefer specific reviews over generic praise or blame. - Downweight generic praise, generic criticism, shipping-only comments, and suspiciously promotional wording. - Group signals into useful themes. - Separate repeated issues from isolated complaints. - Weigh severity as well as frequency.

  1. If Mode 2, do not fake completion.

- State that public review evidence is not sufficiently accessible. - Explain the limitation briefly. - Give only a limited conclusion when still useful. - Do not pretend to have validated real review sentiment.

  1. Give the final answer.

Cover: - verdict - what evidence was actually available - buyer fit when supportable - main positives and risks when supportable - what to verify before buying - confidence

Output

Use this structure unless the user asks for something else.

Mode 1 output

Use when public review evidence is available.

Overall Verdict

Choose one:

  • Recommend
  • Recommend with caveats
  • Depends on use case
  • Not recommended
  • Not enough evidence for a strong recommendation

Why

2-4 bullets with the strongest evidence.

Best For

Who is most likely to be satisfied.

Main Positives

Most credible repeated strengths.

Main Risks

Most important risks, including repeated issues or severe but less frequent ones.

Watch Before Buying

What the buyer should verify before ordering.

Final Advice

A direct recommendation in plain language.

Confidence

High / Medium / Low, with a brief reason.

Mode 2 output

Use when public review evidence is not sufficiently accessible.

Overall Verdict

Usually:

  • Not enough evidence for a strong recommendation
  • Depends on use case

Why

Explain what was and was not accessible.

Current Limitation

State whether the issue is platform blocking, weak public text, ambiguous product matching, or incomplete review visibility.

Watch Before Buying

State what remains unverified.

Final Advice

Give a cautious conclusion without pretending the reviews were validated.

Confidence

Usually Low.

Quality bar

Do:

  • lead with the verdict
  • use representative evidence
  • explain trade-offs clearly
  • say who the product is for
  • lower confidence when evidence is weak

Do not:

  • summarize without recommending
  • rely on only one review slice
  • overreact to one dramatic review
  • overstate certainty
  • invent facts not supported by visible evidence

Limitation handling

If the product cannot be identified confidently:

  • ask one short clarifying question

If the platform does not expose enough public review content:

  • switch to Mode 2
  • state the limitation briefly
  • keep confidence low

If public review evidence is sparse or mixed but still partially usable:

  • stay in Mode 1 only if a limited review-based judgment is still supportable
  • lower confidence
  • narrow the claim

If reviews may mix multiple variants:

  • mention that risk
  • avoid overly specific claims unless the variant is clear

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

76.51%
按下载量换算1,620

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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