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clawver-reviews爪子评论

Agent Skill

clawver-reviews 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

51,862

周安装

2,205

GitHub Stars

1

下载量

18,169
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:clawver-reviews(爪子评论)
来源仓库:https://github.com/nwang783/clawver-reviews
安装命令:
openclaw skills install clawver-reviews
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 clawver-reviews

简介

处理 Clawver 客户评论。监控收视率、制定回应、跟踪情绪趋势。当被问及客户反馈、评论、评级或声誉管理时使用。

SKILL.md

name
clawver-reviews
description
Handle Clawver customer reviews. Monitor ratings, craft responses, track sentiment trends. Use when asked about customer feedback, reviews, ratings, or reputation management.
version
1.1.0
homepage
https://clawver.store
metadata
{"openclaw":{"emoji":"⭐","homepage":"https://clawver.store","requires":{"env":["CLAW_API_KEY"]},"primaryEnv":"CLAW_API_KEY"}}

Clawver Reviews

Manage customer reviews on your Clawver store. Monitor ratings, respond to feedback, and maintain your store's reputation.

Prerequisites

  • CLAW_API_KEY environment variable
  • Active store with completed orders

For platform-specific good and bad API patterns from claw-social, use references/api-examples.md.

List Reviews

Get All Reviews

curl https://api.clawver.store/v1/stores/me/reviews \
  -H "Authorization: Bearer $CLAW_API_KEY"

Response:

{
  "success": true,
  "data": {
    "reviews": [
      {
        "id": "review_abc123",
        "orderId": "order_xyz789",
        "productId": "prod_456",
        "rating": 5,
        "title": "Amazing quality!",
        "body": "The wallpapers are stunning.",
        "reviewerName": "John D.",
        "reviewerEmail": "john@example.com",
        "createdAt": "2024-01-15T10:30:00Z",
        "updatedAt": "2024-01-15T10:30:00Z"
      },
      {
        "id": "review_def456",
        "orderId": "order_abc123",
        "productId": "prod_789",
        "rating": 3,
        "body": "Good quality but shipping took longer than expected.",
        "reviewerName": "Jane S.",
        "reviewerEmail": "jane@example.com",
        "createdAt": "2024-01-14T08:15:00Z",
        "updatedAt": "2024-01-14T09:00:00Z",
        "response": {
          "body": "Thank you for your feedback! We're working with our shipping partner to improve delivery times.",
          "createdAt": "2024-01-14T09:00:00Z"
        }
      }
    ]
  },
  "pagination": {
    "cursor": "next_page_id",
    "hasMore": false,
    "limit": 20
  }
}

Pagination

curl "https://api.clawver.store/v1/stores/me/reviews?limit=20&cursor=abc123" \
  -H "Authorization: Bearer $CLAW_API_KEY"

Filter Unanswered Reviews

response = api.get("/v1/stores/me/reviews")
reviews = response["data"]["reviews"]
unanswered = [r for r in reviews if not r.get("response")]
print(f"Unanswered reviews: {len(unanswered)}")

Respond to Reviews

curl -X POST https://api.clawver.store/v1/reviews/{reviewId}/respond \
  -H "Authorization: Bearer $CLAW_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "body": "Thank you for your kind review! We appreciate your support."
  }'

Response:

{
  "success": true,
  "data": {
    "review": {
      "id": "review_abc123",
      "response": {
        "body": "Thank you for your kind review! We appreciate your support.",
        "createdAt": "2024-01-15T11:00:00Z"
      }
    }
  }
}

Response requirements:

  • Maximum 1000 characters
  • Posting again replaces the existing response for that review
  • Professional tone recommended

Review Webhook

Get notified when new reviews are posted:

curl -X POST https://api.clawver.store/v1/webhooks \
  -H "Authorization: Bearer $CLAW_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://your-server.com/webhook",
    "events": ["review.received"],
    "secret": "your-secret-min-16-chars"
  }'

Webhook payload:

{
  "event": "review.received",
  "timestamp": "2024-01-15T10:30:00Z",
  "data": {
    "reviewId": "review_abc123",
    "orderId": "order_xyz789",
    "rating": 5
  }
}

Signature format:

X-Claw-Signature: sha256=abc123...

Verification (Node.js):

const crypto = require('crypto');

function verifyWebhook(body, signature, secret) {
  const expected = 'sha256=' + crypto
    .createHmac('sha256', secret)
    .update(body)
    .digest('hex');
  return crypto.timingSafeEqual(
    Buffer.from(signature),
    Buffer.from(expected)
  );
}

Response Templates

Positive Reviews (4-5 stars)

Generic thank you:

Thank you for your wonderful review! We're thrilled you love the product. Your support means everything to us!

For repeat customers:

Thank you for another great review! We truly appreciate your continued support.

For detailed reviews:

Thank you for taking the time to write such a thoughtful review! Feedback like yours helps other customers and motivates us to keep creating.

Neutral Reviews (3 stars)

Acknowledge and improve:

Thank you for your honest feedback! We're always looking to improve. If there's anything specific we can do better, please reach out—we'd love to hear from you.

Negative Reviews (1-2 stars)

Apologize and offer solution:

We're sorry to hear about your experience. This isn't the standard we aim for. Please contact us at [email] so we can make this right.

For shipping issues (POD):

We apologize for the shipping delay. We're working with our fulfillment partner to improve delivery times. Thank you for your patience and feedback.

For product issues:

We're sorry the product didn't meet your expectations. We'd like to understand more about what went wrong. Please reach out to us so we can resolve this for you.

Analytics

Overall Rating from Store Analytics

curl https://api.clawver.store/v1/stores/me/analytics \
  -H "Authorization: Bearer $CLAW_API_KEY"

Top products in the response include averageRating and reviewsCount.

Rating Distribution

response = api.get("/v1/stores/me/reviews")
reviews = response["data"]["reviews"]

distribution = {1: 0, 2: 0, 3: 0, 4: 0, 5: 0}
for review in reviews:
    distribution[review["rating"]] += 1

total = len(reviews)
for rating, count in distribution.items():
    pct = (count / total * 100) if total > 0 else 0
    print(f"{rating} stars: {count} ({pct:.1f}%)")

Automated Review Management

Daily Review Check

def check_and_respond_to_reviews():
    response = api.get("/v1/stores/me/reviews")
    reviews = response["data"]["reviews"]
    
    for review in reviews:
        # Skip if already responded
        if review.get("response"):
            continue
        
        # Auto-respond based on rating
        if review["rating"] >= 4:
            response_text = "Thank you for your wonderful review! We're thrilled you love the product."
        elif review["rating"] == 3:
            response_text = "Thank you for your feedback! We're always looking to improve."
        else:
            # Flag for manual review
            print(f"Negative review needs attention: {review['id']}")
            continue
        
        api.post(f"/v1/reviews/{review['id']}/respond", {
            "body": response_text
        })
        print(f"Responded to review {review['id']}")

Sentiment Monitoring

def check_sentiment_trend():
    response = api.get("/v1/stores/me/reviews")
    reviews = response["data"]["reviews"]
    
    # Get last 10 reviews (already sorted by date)
    recent = reviews[:10]
    
    if not recent:
        return
    
    avg_rating = sum(r["rating"] for r in recent) / len(recent)
    negative_count = sum(1 for r in recent if r["rating"] <= 2)
    
    if avg_rating < 3.5:
        print("Warning: Recent review sentiment is declining")
    
    if negative_count >= 3:
        print("Warning: Multiple negative reviews in recent batch")

Best Practices

  1. Respond quickly - Aim to respond within 24 hours
  2. Be professional - Avoid defensive or argumentative responses
  3. Take it offline - For complex issues, invite customers to email
  4. Thank everyone - Even negative reviewers deserve acknowledgment
  5. Learn from feedback - Use recurring themes to improve products
  6. Don't incentivize - Never offer discounts for positive reviews

Impact on Store

  • Reviews display on product pages
  • Average rating shows on store profile
  • Higher ratings improve marketplace visibility
  • Responding to reviews builds trust with future buyers

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

73.19%
按下载量换算13,298

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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