Agent skill · Testing & QA

multi-search-engine

Query the web through multiple search engines (Brave, Tavily, SerpAPI, DuckDuckGo, Bing, Baidu, Sogou, 360) with a single CLI surface. Trigger when the user asks for a research search, fact lookup, source discovery, or wants to compare engines for coverage. The skill aggregates per-engine result lists and normalizes them into a uniform JSON shape for downstream skills (deep-research is the primary consumer). API-key engines gate themselves on the relevant environment variable; engines requiring no key always run.

opensquilla6,385★ · +160/wk · 1 repos on radarProfile →
claude-codeships scriptsApache-2.0
Install
npx skills add opensquilla/opensquilla --skill multi-search-engine --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 4 KB
Bundled scripts: yes
Path: src/opensquilla/skills/bundled/multi-search-engine/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 6,515 · +130 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# multi-search-engine A unified CLI for querying several web search engines in parallel and returning a normalized result list. Built on `httpx` and `beautifulsoup4` (both already in OpenSquilla default dependencies, so no extra install beyond `pip install opensquilla`). ## Use cases - Building a `deep-research` round with diverse engine coverage - Fact-check a claim against >1 engine - Compare what Bing returns vs DuckDuckGo for the same query - Search Chinese-language sources via Baidu/Sogou/360 alongside global engines ## Limitations - A single engine sufficient → call its API directly instead - Need headless-browser DOM rendering → this skill is HTTP-only ## Quick start ```bash python {baseDir}/scripts/search.py \ --query "openclaw skill registry" \ --engines duckduckgo,brave \ --limit 10 \ --json ``` Output: ```json { "query": "...", "results": [ { "engine": "duckduckgo", "title": "...", "url": "https://...", "snippet": "...", "rank": 1 } ], "errors": [ {"engine": "brave", "reason": "BRAVE_SEARCH_API_KEY/BRAVE_API_KEY not set; skipping"} ] } ``` ## Engines | Engine | Needs key | Key env var | Strength | |---|---|---|---| | `duckduckgo` | no | — | Privacy-friendly, no rate limi

What's inside
Steps it walks through
  1. Use cases
  2. Limitations
  3. Quick start
  4. Engines
  5. Routing tips
  6. Boundaries
Ships with 3 files
  • THIRD_PARTY_NOTICES.md
  • references/engines.md
  • scripts/search.py
Commands it runs
python {baseDir}/scripts/search.py \
More from opensquilla
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About this skill
What does the multi-search-engine skill do?

Query the web through multiple search engines (Brave, Tavily, SerpAPI, DuckDuckGo, Bing, Baidu, Sogou, 360) with a single CLI surface. Trigger when the user asks for a research search, fact lookup, source discovery, or wants to compare engines for coverage. The skill aggregates per-engine result lists and normalizes them into a uniform JSON shape for downstream skills (deep-research is the primary consumer). API-key engines gate themselves on the relevant environment variable; engines requiring no key always run.

How do I install it?

Run `npx skills add opensquilla/opensquilla --skill multi-search-engine --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From opensquilla/opensquilla, a repository with 6,515 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going