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ddgs-search

Free multi-engine web search via ddgs CLI (DuckDuckGo, Google, Bing, Brave, Yandex, Yahoo, Wikipedia) + arXiv API search. No API keys required. Use when user needs web search, research paper discovery, or when other skills need a search backend. Drop-in replacement for web-search-plus.

camopel0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install camopel/ddgs-search

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

ddgs-search

Why This Skill?

🆓 Completely free — no API keys, no subscriptions, no rate limits, no billing surprises.

🔍 8 search engines in one — Google, Bing, DuckDuckGo, Brave, Yandex, Yahoo, Wikipedia, and Mojeek. Switch engines with a single flag. Most search skills only support one.

🎓 Built-in arXiv research search — search academic papers directly via arXiv's free API. Returns authors, categories, abstracts, and publication dates. Perfect for researchers, students, and AI/ML practitioners.

🔌 Drop-in replacement — outputs web-search-plus compatible JSON, so it works with any skill or tool that expects that format. Zero config migration.

⚡ Lightweight — single pip package, no browser automation, no headless Chrome. Searches complete in 1-3 seconds.

Install

python3 scripts/install.py

Works on macOS, Linux, and Windows. Installs the ddgs package, verifies CLI access, and runs a quick search test.

Manual install
pip install ddgs

Web Search

CLI wrapper (recommended)

The ddgs-search wrapper outputs clean JSON to stdout with no interactive prompts or abort issues:

# Google (default)
ddgs-search "your query" 5 google

# Other engines
ddgs-search "your query" 3 duckduckgo
ddgs-search "your query" 5 brave
ddgs-search "your query" 10 yandex
Python script (web-search-plus compatible JSON)
# Google (default)
python3 scripts/search.py -q "your query" -m 5

# Other engines
python3 scripts/search.py -q "your query" -b duckduckgo
python3 scripts/search.py -q "your query" -b brave
python3 scripts/search.py -q "your query" -b yandex
python3 scripts/search.py -q "your query" -b yahoo
python3 scripts/search.py -q "your query" -b wikipedia

Output (web-search-plus compatible JSON):

{
  "provider": "ddgs",
  "results": [
    {"title": "...", "url": "...", "snippet": "...", "published_date": "..."}
  ]
}

arXiv Search

# Search by topic
python3...

Source information

Source
github
Repository
openclaw/skills
Path
skills/camopel/ddgs-search
Version
—
Commit
29ba6a20af440944c9a654aaa8f4db4887cc1b94
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

README

ddgs-search

Free multi-engine web search skill for OpenClaw agents. No API keys required.

Supports: Google, Bing, DuckDuckGo, Brave, Yandex, Yahoo, Wikipedia + arXiv API for academic papers.

Install

python3 scripts/install.py

Installs the ddgs Python package and verifies the CLI is accessible.

Scripts

scripts/search.py — Web search
python3 scripts/search.py -q "your query" -m 5
python3 scripts/search.py -q "AI news" -m 10 -b bing
python3 scripts/search.py -q "python tutorial" -m 5 -b google

Options:

Flag Description Default
-q Search query (required)
-m Max results 5
-b Backend: duckduckgo, google, bing, brave, yandex, yahoo duckduckgo

Output: JSON with results array of {title, url, snippet}.

scripts/arxiv_search.py — arXiv paper search
python3 scripts/arxiv_search.py -q "transformer architecture" -m 10
python3 scripts/arxiv_search.py -q "diffusion models" -m 5 --sort-by relevance

Options:

Flag Description Default
-q Search query (required)
-m Max results 10
--sort-by relevance or date relevance

Output: JSON with results array including arxiv_id, title, abstract, authors, published, pdf_url.

Usage in OpenClaw

The skill is registered with OpenClaw and provides two tools:

  • web_search — Search the web across multiple engines
  • arxiv_search — Search academic papers on arXiv

Requirements

  • Python 3.8+
  • ddgs package (installed automatically)
  • macOS or Linux (Windows: partial support)

License

MIT

Extracted content

SKILL.md
# ddgs-search

## Why This Skill?

🆓 **Completely free** — no API keys, no subscriptions, no rate limits, no billing surprises.

🔍 **8 search engines in one** — Google, Bing, DuckDuckGo, Brave, Yandex, Yahoo, Wikipedia, and Mojeek. Switch engines with a single flag. Most search skills only support one.

🎓 **Built-in arXiv research search** — search academic papers directly via arXiv's free API. Returns authors, categories, abstracts, and publication dates. Perfect for researchers, students, and AI/ML practitioners.

🔌 **Drop-in replacement** — outputs web-search-plus compatible JSON, so it works with any skill or tool that expects that format. Zero config migration.

⚡ **Lightweight** — single pip package, no browser automation, no headless Chrome. Searches complete in 1-3 seconds.

## Install

```bash
python3 scripts/install.py
```

Works on **macOS, Linux, and Windows**. Installs the `ddgs` package, verifies CLI access, and runs a quick search test.

### Manual install
```bash
pip install ddgs
```

## Web Search

### CLI wrapper (recommended)

The `ddgs-search` wrapper outputs clean JSON to stdout with no interactive prompts or abort issues:

```bash
# Google (default)
ddgs-search "your query" 5 google

# Other engines
ddgs-search "your query" 3 duckduckgo
ddgs-search "your query" 5 brave
ddgs-search "your query" 10 yandex
```

### Python script (web-search-plus compatible JSON)

```bash
# Google (default)
python3 scripts/search.py -q "your query" -m 5

# Other engines
python3 scripts/search.py -q "your query" -b duckduckgo
python3 scripts/search.py -q "your query" -b brave
python3 scripts/search.py -q "your query" -b yandex
python3 scripts/search.py -q "your query" -b yahoo
python3 scripts/search.py -q "your query" -b wikipedia
```

Output (web-search-plus compatible JSON):
```json
{
  "provider": "ddgs",
  "results": [
    {"title": "...", "url": "...", "snippet": "...", "published_date": "..."}
  ]
}
```

## arXiv Search

```bash
# Search by topic
python3...
README
# ddgs-search

Free multi-engine web search skill for [OpenClaw](https://github.com/camopel/openclaw) agents. No API keys required.

Supports: **Google, Bing, DuckDuckGo, Brave, Yandex, Yahoo, Wikipedia** + **arXiv API** for academic papers.

## Install

```bash
python3 scripts/install.py
```

Installs the `ddgs` Python package and verifies the CLI is accessible.

## Scripts

### `scripts/search.py` — Web search

```bash
python3 scripts/search.py -q "your query" -m 5
python3 scripts/search.py -q "AI news" -m 10 -b bing
python3 scripts/search.py -q "python tutorial" -m 5 -b google
```

**Options:**
| Flag | Description | Default |
|------|-------------|---------|
| `-q` | Search query | (required) |
| `-m` | Max results | 5 |
| `-b` | Backend: `duckduckgo`, `google`, `bing`, `brave`, `yandex`, `yahoo` | `duckduckgo` |

**Output:** JSON with `results` array of `{title, url, snippet}`.

### `scripts/arxiv_search.py` — arXiv paper search

```bash
python3 scripts/arxiv_search.py -q "transformer architecture" -m 10
python3 scripts/arxiv_search.py -q "diffusion models" -m 5 --sort-by relevance
```

**Options:**
| Flag | Description | Default |
|------|-------------|---------|
| `-q` | Search query | (required) |
| `-m` | Max results | 10 |
| `--sort-by` | `relevance` or `date` | `relevance` |

**Output:** JSON with `results` array including `arxiv_id`, `title`, `abstract`, `authors`, `published`, `pdf_url`.

## Usage in OpenClaw

The skill is registered with OpenClaw and provides two tools:

- **`web_search`** — Search the web across multiple engines
- **`arxiv_search`** — Search academic papers on arXiv

## Requirements

- Python 3.8+
- `ddgs` package (installed automatically)
- macOS or Linux (Windows: partial support)

## License

MIT

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