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Agent Skill · 研究检索

bright-data(明亮的数据)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

bright-data 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 35,709。

总安装 2,040周安装 85GitHub Stars 56下载 680核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:bright-data(明亮的数据)
来源仓库:https://github.com/vm0-ai/vm0-skills
仓库路径:skills/bright-data
安装命令:
npx skills add https://github.com/vm0-ai/vm0-skills --skill bright-data
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/vm0-ai/vm0-skills --skill bright-data

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

bright-data 通过 Bright Data API 触发异步数据整理,支持社交媒体等平台爬取。适用于舆情监控、竞品分析与市场调研。需先配置 CLI 认证与 zone 设置方可调用。使用前应确认目标网站反爬政策与数据使用合规性。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/bright-data

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/vm0-ai/vm0-skills --skill bright-data;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

bright-data 怎么安装?

在终端执行 npx skills add https://github.com/vm0-ai/vm0-skills --skill bright-data。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

bright-data 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

bright-data 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

bright-data 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

bright-data 用的人多吗?

公开数据是累计安装 2,040 次,近一周安装 85 次,下载 680 次,GitHub 56 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

bright-data 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
bright-data

明亮的数据 · 本页

2,04056需要联网MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Troubleshooting

If requests fail, run zero doctor check-connector --env-name BRIGHTDATA_TOKEN or zero doctor check-connector --url https://api.brightdata.com/datasets/v3/trigger --method POST

Social Media Scraping

Bright Data supports scraping these social media platforms:

PlatformProfilesPostsCommentsReels/Videos
Twitter/X✅✅--
Reddit-✅✅-
YouTube✅✅✅-
Instagram✅✅✅✅
TikTok✅✅✅-
LinkedIn✅✅--

How to Use

1. Trigger Scraping (Asynchronous)

Trigger a data collection job and get a snapshot_id for later retrieval.

Write to /tmp/brightdata_request.json:

[
  {"url": "https://twitter.com/username"},
  {"url": "https://twitter.com/username2"}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/trigger?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

Response:

{
  "snapshot_id": "s_m4x7enmven8djfqak"
}

2. Trigger Scraping (Synchronous)

Get results immediately in the response (for small requests).

Write to /tmp/brightdata_request.json:

[
  {"url": "https://www.reddit.com/r/technology/comments/xxxxx"}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/scrape?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

3. Monitor Progress

Check the status of a scraping job (replace <snapshot-id> with your actual snapshot ID):

curl -s "https://api.brightdata.com/datasets/v3/progress/<snapshot-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN"

Response:

{
  "snapshot_id": "s_m4x7enmven8djfqak",
  "dataset_id": "gd_xxxxx",
  "status": "running"
}

Status values: running, ready, failed

4. Download Results

Once status is ready, download the collected data (replace <snapshot-id> with your actual snapshot ID):

curl -s "https://api.brightdata.com/datasets/v3/snapshot/<snapshot-id>?format=json" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN"

5. List Snapshots

Get all your snapshots:

curl -s "https://api.brightdata.com/datasets/v3/snapshots" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" | jq '.[] | {snapshot_id, dataset_id, status}'

6. Cancel Snapshot

Cancel a running job (replace <snapshot-id> with your actual snapshot ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/cancel?snapshot_id=<snapshot-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN"

Platform-Specific Examples

Twitter/X - Scrape Profile

Write to /tmp/brightdata_request.json:

[
  {"url": "https://twitter.com/elonmusk"}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/scrape?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

Returns: x_id, profile_name, biography, is_verified, followers, following, profile_image_link

Twitter/X - Scrape Posts

Write to /tmp/brightdata_request.json:

[
  {"url": "https://twitter.com/username/status/123456789"}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/scrape?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

Returns: post_id, text, replies, likes, retweets, views, hashtags, media

Reddit - Scrape Subreddit Posts

Write to /tmp/brightdata_request.json:

[
  {"url": "https://www.reddit.com/r/technology", "sort_by": "hot"}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/trigger?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

Parameters: url, sort_by (new/top/hot)

Returns: post_id, title, description, num_comments, upvotes, date_posted, community

Reddit - Scrape Comments

Write to /tmp/brightdata_request.json:

[
  {"url": "https://www.reddit.com/r/technology/comments/xxxxx/post_title"}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/scrape?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

Returns: comment_id, user_posted, comment_text, upvotes, replies

YouTube - Scrape Video Info

Write to /tmp/brightdata_request.json:

[
  {"url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ"}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/scrape?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

Returns: title, views, likes, num_comments, video_length, transcript, channel_name

YouTube - Search by Keyword

Write to /tmp/brightdata_request.json:

[
  {"keyword": "artificial intelligence", "num_of_posts": 50}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/trigger?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

YouTube - Scrape Comments

Write to /tmp/brightdata_request.json:

[
  {"url": "https://www.youtube.com/watch?v=xxxxx", "load_replies": 3}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/scrape?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

Returns: comment_text, likes, replies, username, date

Instagram - Scrape Profile

Write to /tmp/brightdata_request.json:

[
  {"url": "https://www.instagram.com/username"}
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/scrape?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

Returns: followers, post_count, profile_name, is_verified, biography

Instagram - Scrape Posts

Write to /tmp/brightdata_request.json:

[
  {
    "url": "https://www.instagram.com/username",
    "num_of_posts": 20,
    "start_date": "01-01-2024",
    "end_date": "12-31-2024"
  }
]

Then run (replace <dataset-id> with your actual dataset ID):

curl -s -X POST "https://api.brightdata.com/datasets/v3/trigger?dataset_id=<dataset-id>" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" \
  -H "Content-Type: application/json" \
  -d @/tmp/brightdata_request.json

Account Management

Check Account Status

curl -s "https://api.brightdata.com/status" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN"

Response:

{
  "status": "active",
  "customer": "hl_xxxxxxxx",
  "can_make_requests": true,
  "ip": "x.x.x.x"
}

Get Active Zones

curl -s "https://api.brightdata.com/zone/get_active_zones" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN" | jq '.[] | {name, type}'

Get Bandwidth Usage

curl -s "https://api.brightdata.com/customer/bw" \
  -H "Authorization: Bearer $BRIGHTDATA_TOKEN"

Getting Dataset IDs

To use the scraping features, you need a dataset_id:

  1. Go to Bright Data Control Panel
  2. Create a new Web Scraper dataset or select an existing one
  3. Choose the platform (Twitter, Reddit, YouTube, etc.)
  4. Copy the dataset_id from the dataset settings

Dataset IDs can also be found in the bandwidth usage API response under the data field keys (e.g., v__ds_api_gd_xxxxx where gd_xxxxx is your dataset ID).

Common Parameters

ParameterDescriptionExample
urlTarget URL to scrapehttps://twitter.com/user
keywordSearch keyword"artificial intelligence"
num_of_postsLimit number of results50
start_dateFilter by date (MM-DD-YYYY)"01-01-2024"
end_dateFilter by date (MM-DD-YYYY)"12-31-2024"
sort_bySort order (Reddit)new, top, hot
formatResponse formatjson, csv

Rate Limits

  • Batch mode: up to 100 concurrent requests
  • Maximum input size: 1GB per batch
  • Exceeding limits returns 429 error

Guidelines

  1. Create datasets first: Use the Control Panel to create scraper datasets
  2. Use async for large jobs: Use /trigger for discovery and batch operations
  3. Use sync for small jobs: Use /scrape for single URL quick lookups
  4. Check status before download: Poll /progress until status is ready
  5. Respect rate limits: Don't exceed 100 concurrent requests
  6. Date format: Use MM-DD-YYYY for date parameters

平台分布

Claude Code

28.89%
按下载量换算196

OpenCode

20.46%
按下载量换算139

Antigravity

18.82%
按下载量换算128

Gemini CLI

12.23%
按下载量换算83

windsurf

7.01%
按下载量换算48

Codex

3.47%
按下载量换算24

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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