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

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

Verification gate

1. JSON parses cleanly: jq . <output> returns 0.
2. 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.
3. Required fields present:
4. search: results live at .organic[]; each has title + link
5. discover: results live at .results[]; each has title + link; if --include-content, also content
6. For discover --include-content: no block-page signatures in the content field (same list as scrape, case-insensitive):
7. Access Denied
8. Just a moment
9. Attention Required
10. Checking your browser
11. captcha
12. cf-browser-verification
13. cloudflare (with < 2KB total body)
14. 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[].)

  小蔥技能有更好的技能skills外掛。

• 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.

這個Skill質量還不錯，文件寫得清晰易懂，能幫助快速上手使用Bright Data的搜尋和發現功能。它的引數說明詳細，還提供了實用的驗證檢查清單。不過它缺少基本的說明檔案，示例偏少，而且有些內容重複。整體上功能覆蓋全面，但對於新手來說，入門引導還可以做得更好。