Openclaw Research Tool
by @aaronn
Search the web using LLMs via OpenRouter. Use for current web data, API docs, market research, news, fact-checking, or any question that benefits from live i...
clawhub install openclaw-search-toolπ About This Skill
name: research-tool description: Search the web using LLMs via OpenRouter. Use for current web data, API docs, market research, news, fact-checking, or any question that benefits from live internet access and reasoning. metadata: {"openclaw": {"emoji": "π", "requires": {"bins": ["research-tool"], "env": ["OPENROUTER_API_KEY"]}, "primaryEnv": "OPENROUTER_API_KEY", "homepage": "https://github.com/aaronn/openclaw-search-tool"}}
OpenClaw Research Tool
Web search for OpenClaw agents, powered by OpenRouter. Ask questions in natural language, get accurate answers with cited sources. Defaults to GPT-5.2 which excels at documentation lookups and citation-heavy research.
> Note: Even low-effort queries may take 1 minute or more to complete. High/xhigh reasoning can take 10+ minutes depending on complexity. This is normal β the model is searching the web, reading pages, and synthesizing an answer. > > Recommended: Run research-tool in a sub-agent so your main session stays responsive: >
> sessions_spawn task:"research-tool 'your query here'"
> yieldMs to background it, then poll β but do NOT set timeout or the process will be killed mid-search.The :online model suffix gives any model live web access β it searches the web, reads pages, cites URLs, and synthesizes an answer.
Install
cargo install openclaw-search-tool
Requires OPENROUTER_API_KEY env var. Get a key at https://openrouter.ai/keys
Quick start
research-tool "What are the x.com API rate limits?"
research-tool "How do I set reasoning effort parameters on OpenRouter?"
From an OpenClaw agent
# Best: run in a sub-agent (main session stays responsive)
sessions_spawn task:"research-tool 'your query here'"Or via exec β NEVER set timeout, use yieldMs to background:
exec command:"research-tool 'your query'" yieldMs:5000
then poll the session until complete
Flags
--effort, -e (default: low)
Controls how much the model reasons before answering. Higher effort means better analysis but slower and more tokens.
research-tool --effort low "What year was Rust 1.0 released?"
research-tool --effort medium "Explain how OpenRouter routes requests to different model providers"
research-tool --effort high "Compare tradeoffs between Opus 4.6 and gpt-5.3-codex for programming"
research-tool --effort xhigh "Deep analysis of React Server Components vs traditional SSR approaches"
| Level | Speed | When to use |
|-------|-------|-------------|
| low | ~1-3 min | Quick fact lookups, simple questions |
| medium | ~2-5 min | Standard research, moderate analysis |
| high | ~3-10 min | Deep analysis with careful reasoning |
| xhigh | ~5-20+ min | Maximum reasoning, complex multi-source synthesis |
Can also be set via env var RESEARCH_EFFORT.
--model, -m (default: openai/gpt-5.2:online)
Which model to use. Defaults to GPT-5.2 with the :online suffix because it excels at questions where citations and accurate documentation lookups matter. The :online suffix enables live web search and works with any model on OpenRouter.
# Default: GPT-5.2 with web search (great for docs and cited answers)
research-tool "current weather in San Francisco"Claude with web search
research-tool -m "anthropic/claude-sonnet-4-20250514:online" "Summarize recent changes to the OpenAI API"GPT-5.2 without web search (training data only)
research-tool -m "openai/gpt-5.2" "Explain the React Server Components architecture"Any OpenRouter model
research-tool -m "google/gemini-2.5-pro:online" "Compare React vs Svelte in 2026"
Can also be set via env var RESEARCH_MODEL.
--system, -s
Override the system prompt to give the model a specific persona or instructions.
research-tool -s "You are a senior infrastructure engineer" "Best practices for zero-downtime Kubernetes deployments"
research-tool -s "You are a Rust systems programmer" "Best async patterns for WebSocket servers"
--stdin
Read the query from stdin. Useful for long or multiline queries.
echo "Explain the OpenRouter model routing architecture" | research-tool --stdin
cat detailed-prompt.txt | research-tool --stdin
--max-tokens (default: 12800)
Maximum tokens in the response.
--timeout (optional, no default)
No timeout by default β queries run until the model finishes. Set this only if you need a hard upper bound (e.g. --timeout 300).
Output format
π Researching with openai/gpt-5.2:online (effort: high)...
β
Connected β waiting for response...[response text on stdout]
π Tokens: 4470 prompt + 184 completion = 4654 total | β± 5s
Status indicators
π Researching... β request sent to OpenRouterβ
Connected β waiting for response... β server accepted the request, model is searching/thinkingβ³ 15s... β³ 30s... β elapsed time ticks (only in interactive terminals, not in agent exec)β Connection to OpenRouter failed β couldn't reach OpenRouter (network issue)β Connection to OpenRouter lost β connection dropped while waiting. Retry?Tips for better results
low for quick facts, high for real research, xhigh only for complex multi-source analysis.-s for domain expertise. A specific persona produces noticeably better domain-specific answers.Cost
~$0.01β0.05 per query. Token usage is printed to stderr after each query.
π‘ Examples
research-tool "What are the x.com API rate limits?"
research-tool "How do I set reasoning effort parameters on OpenRouter?"
From an OpenClaw agent
# Best: run in a sub-agent (main session stays responsive)
sessions_spawn task:"research-tool 'your query here'"Or via exec β NEVER set timeout, use yieldMs to background:
exec command:"research-tool 'your query'" yieldMs:5000
then poll the session until complete