Skills Plugins MCP Prompt Model 博客 我的中心
开发编程 #data #api #web

search

Search the web via the Bright Data CLI — `bdata search` for Google/Bing/Yandex SERP, `bdata discover` for intent-ranked semantic results. Use when the user wants SERP results, needs URLs to feed into scraping, or wants semantic web discovery with optional page content. Hands off to `scrape` once target URLs are chosen, and to `data-feeds` when the user wants structured data from a known platform. Requires the Bright Data CLI; proactively guides install + login if missing.

DeepseekModel 官方收录技能 质量 优秀 · 78 v1.0.0

获取

https://deepseekmodel.com/api/download.php?id=brightdata-skills-skills-search-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name search description Search the web via the Bright Data CLI — `bdata search` for Google/Bing/Yandex SERP, `bdata discover` for intent-ranked semantic results. Use when the user wants SERP results, needs URLs to feed into scraping, or wants semantic web discovery with optional page content. Hands off to `scrape` once target URLs are chosen, and to `data-feeds` when the user wants structured data from a known platform. Requires the Bright Data CLI; proactively guides install + login if missing. Bright Data — Search Find things on the web. Two commands live in this skill: bdata search — classic keyword SERP (Google/Bing/Yandex). Best when you want "what ranks for keyword X." bdata discover — AI intent-ranked discovery with optional page content. Best when you want "pages about topic Y that match intent Z." For structured data from a known platform (Amazon, LinkedIn, TikTok, …), stop and use data-feeds instead . Setup gate (run first) if ! command -v bdata >/dev/null 2>&1; then echo "bdata CLI not installed — see bright-data-best-practices/references/cli-setup.md" elif ! bdata zones >/dev/null 2>&1; then echo "bdata not authenticated — run: bdata login (or: bdata login --device for SSH)" fi Halt and route to skills/bright-data-best-practices/references/cli-setup.md if either check fails. Pick your path Situation Action Single keyword query, just SERP bdata search "<query>" --engine google --json --pretty Paginated SERP (more results) loop --page 0 , --page 1 , … (0-indexed) Multiple queries shell loop over a queries file Intent-ranked / semantic (not keyword) bdata discover "<query>" --intent "<intent>" --num-results 20 Want page bodies along with results, one pass bdata discover ... --include-content News / images / shopping SERP bdata search "<query>" --type news (or images , shopping ) Want Amazon/LinkedIn/TikTok/… structured data stop — hand off to data-feeds Have URLs, want content hand off to scrape Action Core commands: # Google SERP, structured JSON bdata search "site:example.com privacy policy" --engine google --json --pretty # Localized Bing (German results, German language) bdata search "datenschutz" --engine bing --country de --language de --json # Second page of results (0-indexed) bdata search "machine learning papers" --page 1 --json # Mobile SERP (rankings differ from desktop) bdata search "best coffee shops" --device mobile --json # News vertical bdata search "openai" -- type news --json --pretty # Intent-ranked discovery bdata discover "enterprise LLM platforms" \ --intent "vendor pages with pricing" \ --num-results 15 --json # Discovery with page content in markdown bdata discover "webhook best practices" \ --include-content --num-results 10 -o results.json # Date-filtered discovery bdata discover "react server components" \ --start-date 2025-01-01 --end-date 2025-12-31 --num-results 20 Full flag reference: references/flags.md . search vs discover — pick the right one You want Use "What Google ranks for this exact keyword" search "Pages that match this meaning/intent" discover "News / images / shopping vertical SERP" search --type <vertical> "Results + page bodies in one call" discover --include-content "Dedup / semantic ranking across queries" discover Verification gate JSON parses cleanly: jq . <output> returns 0. Result array non-empty — if empty, the query is legitimately zero-result; relax the query and re-run. Don't claim success on empty results without telling the user. Required fields present: search : results live at .organic[] ; each has title + link discover : results live at .results[] ; each has title + link ; if --include-content , also content For discover --include-content : no block-page signatures in the content field (same list as scrape, case-insensitive): Access Denied Just a moment Attention Required Checking your browser captcha cf-browser-verification cloudflare (with < 2KB total body) Geo sanity: if the user expected country-specific results, inspect TLDs / languages of top results. If mis-localized, re-run with explicit --country and --language . Red flags Using search to fetch content from Amazon, LinkedIn, TikTok, etc. when data-feeds returns clean structured data in one call. Scraping every SERP result blindly — filter first (domain allowlist, keyword in title, relevance heuristic). Confusing search (keyword) with discover (semantic). They answer different questions. Running multiple queries without deduping URLs across result sets before scraping. Assuming SERP order is universal — it's personalized by geo + device. Always set --country and --device explicitly for reproducibility. Using --page as a result count — it's a page index, not a limit. Each page returns ~10 results. Assuming SERP results are at .results[] — for bdata search they live at .organic[] . (Discover uses .results[] .) Hardcoding --num-results 100 on discover without realizing the pipeline polls until that many are found; can be slow. References references/flags.md — full flags for search and discover with when-to-use notes. references/patterns.md — multi-query dedup, SERP → filter → scrape pipeline, search vs discover decision, legacy curl fallback, shared verification checklist. references/examples.md — (1) single Google query, (2) localized Bing, (3) batch queries + dedup into URL list, (4) discover --include-content end-to-end.
Agent 识别该技能的关键词,点击任意一个即可复制。

该技能未提供触发词。

下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

每日精选 Skill 推荐,免费送到你邮箱

输入邮箱,每天接收一个精选 AI Agent 技能推荐。完全免费,持续更新。

验证码 --

提交后我们会发送一封确认邮件,点击邮件里的链接才会开始收信。

完全免费,取消任意时间。我们不会发送垃圾邮件。