Search & research
Research & knowledge graphs
Multi-step research and structured entity graphs.
research — full research in one command
omniscout research "emerging quantum computing startups 2026"
omniscout research "vector database benchmarks 2026" --results 10One call researches across many sources. Tune it with:
| Flag | Meaning | Default |
|---|---|---|
--results/-k | Sources to use | 8 |
--depth | How thoroughly to explore (1 = overview only) | 1 |
--query/-q | Topic as a flag instead of a positional arg | — |
--summarize / --no-summarize | Include a summary | summarize |
--probe-pro | Better answers for hard questions | off |
--probe | Alternative answer mode | off |
research output pipes cleanly to jq: omniscout research "topic" | jq '.passages[0:3]'.
When to use research vs answer vs extract
answer— one fact, fast.research— a topic you need surveyed across many sources, with passages you can cite.extract— you already know the URL(s); skip the search step. See Extraction.
graph — structured knowledge graphs
omniscout graph "Cursor" # search the web and extract
omniscout graph "Cursor" -w cursor.com # use that site directly
omniscout graph "Cursor" --data # include sources and timing
omniscout graph "Cursor" --llm # optional AI overlay on the resultsgraph maps a company, person, or product into a structured tree of entities and relationships. Pass a bare domain (cursor.com) to stay on-site, or -w/--website to use one site and its internal links. --results/-k controls how many sources are used (default 5).
benchmark — compare answer modes
omniscout benchmark answers
omniscout benchmark retrieval
omniscout benchmark ablation # full ablation matrix with persisted metricsbenchmark compares answer modes against sample questions — useful when deciding between --probe, --classic, and --probe-pro for your workload.
Probe Zero vs Classic
Probe Zero is an answer mode (see omniscout settings engines):
- Probe Zero Mini — good default for direct answers.
- Classic — deterministic, works offline after setup.
- Probe Pro — for the hardest questions.
Compare them with omniscout benchmark answers before standardizing in an agent loop.