| name | searxng-search |
| description | Aggregate web search across 20+ engines (Google, Google Scholar, Semantic Scholar, arXiv, GitHub, Reddit, etc.). Returns titles, URLs, and snippets. Use for: fact lookups, background reading, finding academic papers or citations, locating repos/packages/APIs, checking recent news, and gathering community discussions or comparisons. Trigger keywords: "search," "look up," "find," "查," "搜," "找," "有没有," and similar. Supports category, language, and single-engine selection when the default Google engine is not enough. Do not use for local file search (use grep), repo-level search (use gh CLI), or in-repo doc search.
|
| metadata | {"argument-hint":"searxng-search \"query\" [-n count] [-e engine] [-l lang] [-c category] [-t timeout]"} |
| allowed-tools | Bash |
searxng-search
A web search skill that queries a SearxNG backend. It defaults to Google for
clear, broad web results. Part of a research workflow: find → read → synthesize.
Pair with browser-fetch to read the pages this skill finds.
Input
The primary input is a natural language query. Optional flags adjust scope:
| Flag | Meaning | Example |
|---|
| query | What to search for (required) | "knowledge graph multi-hop reasoning" |
-n | Limit number of results | -n 5 |
-e | Use one specific engine instead of Google | -e google_scholar |
-l | Language preference | -l zh-CN |
-c | Category | -c news |
-t | Request timeout in seconds | -t 60 |
-u | Output URLs only | -u |
-j | Output JSON (structured, for scripting) | -j |
How to invoke
The script is bundled with this skill. Always invoke it via the script path
so it works regardless of whether searxng-search is on the user's PATH:
uv run --script ${SKILL_DIR}/scripts/searxng-search "query"
uv run --script ${SKILL_DIR}/scripts/searxng-search "query" -n 5
uv run --script ${SKILL_DIR}/scripts/searxng-search "query" -e google_scholar
uv run --script ${SKILL_DIR}/scripts/searxng-search "query" -c news -l zh-CN
Do not invoke the script directly (e.g. ${SKILL_DIR}/scripts/searxng-search ...) — the
file may not have execute permission after deployment. Always use uv run --script.
The only external dependency is uv (auto-installs inline Python deps on
first run) and a running SearxNG backend.
Environment
SEARXNG_URL — SearxNG endpoint (default: http://localhost:8082)
WEB_KIT_API_KEY — required; sent as the X-API-Key header to authenticate to the gateway.
Default behavior
If you do not specify any flags:
- Engine: Google
- Results: top 10
- Output: concise human-readable list with title, URL, snippet, and engine tag
- Errors: JSON to stdout with an
error_type field (exit code 1)
Available engines
Engines are grouped by what they index. Choose at most one non-default engine
per search. To compare sources, run separate searches.
The CLI exposes shell-friendly aliases such as google_scholar and
semantic_scholar; the script maps them to SearXNG's configured engine names
such as google scholar and semantic scholar.
| Group | Engines |
|---|
| General | google, bing, duckduckgo |
| Academic | google_scholar, semantic_scholar, openalex, dblp, pubmed, arxiv |
| Code and packages | github, github_code, gitlab, huggingface, npm, pypi, crates, lib_rs, pkg_go_dev, sourcehut, microsoft_learn, nvd |
| Community | hackernews, reddit, wikidata |
| Books and library | annas_archive, zlibrary |
Per-engine usage notes and examples are in references/engines.md.
Typical workflow
-
Start with the default search. The default already indexes a wide range
of sources (paper aggregators, repos, blogs, docs, forums). Often enough to
understand the landscape of a topic.
-
Observe what kind of results appear. If the top results already point to
the right kind of sources (papers, repos, news, forums), you may already
have what you need.
-
If results are not from the expected domain, retry with one
domain-specific engine. For example:
- Academic metadata:
-e google_scholar, then a separate search with
-e semantic_scholar if needed
- Code and packages:
-e github, then a separate search with -e npm or
-e pypi if needed
- Community experience:
-e reddit, then a separate search with
-e hackernews if needed
- News and recent events:
-c news
-
If results are from the right domain but not specific enough, narrow
further — e.g. site:arxiv.org in the query, or point at a specific
source with -e.
How to interpret results
- The default output shows which engine each result came from.
- If results cluster around a particular domain (papers, repos, docs), that
may indicate which single domain-specific engine could be useful next.
- If results are already rich and directly relevant, additional searches may
not add much value.
- A
site: filter is useful when you already know the kind of source you
want, without switching the underlying engine set.
Notes on engine choice
- For academic tasks, dedicated academic engines often provide cleaner
metadata (authors, years, venues, citations). Google already indexes most
major paper sources, so the default is a reasonable first step.
- For code and package tasks, dedicated engines point directly to repos and
package registries, which the default may surface less reliably.
- Some engines (notably arxiv) can be slower or more prone to timeout. If you
do not specifically need arXiv as a source, the default or another academic
engine is often sufficient.
-e accepts exactly one engine. Do not pass comma-separated engine lists;
mixed-engine results are harder to interpret and compare.-e changes which search path is used; it does not just filter the default
results. Prefer default Google first, then one explicit engine per retry.- The default human-readable output is intentionally concise. For structured
results,
-j is available (hidden from default help because it produces
longer output).
Error handling
All errors are JSON to stdout (exit code 1):
{"error_type": "timeout", "query": "...", "hint": "..."}
| error_type | What it means | What is available to you |
|---|
timeout | The request took too long | Try a longer timeout with -t 60 |
no_results | No results came back from the requested engines | Refine the query or try different engines |
http_error | The backend returned an HTTP error | Usually transient |
backend_unreachable | The SearxNG backend could not be reached | Check SEARXNG_URL |
If the command succeeds but an engine failed, the output includes which engine
did not respond — useful for deciding whether to retry with a different engine.
Final output
Depending on how you invoke the skill, you may get:
