Technical comparison
Compare two deployment approaches using official documentation, failure modes, migration costs, operational evidence, and version cutoffs.
Workflows and examples
Begin with a decision, not a source quota.
The most useful request names who will use the result, what they must decide, what belongs in scope, what evidence matters, and what the deliverable must expose.
A representative first request
Use $omnara-deep-research. Investigate whether small organizations should adopt passkeys for customer accounts in 2026. Audience: a product and security lead deciding what to ship. Scope: consumer web accounts in the United States and European Union. Include implementation tradeoffs, recovery, accessibility, adoption evidence, and credible objections. Deliver a decision brief with recommendation, evidence limits, contradictions, source-state counts, audit dispositions, and refresh triggers.Before retrieval, expect the preserved inquiry, audience and decision use, scope and exclusions, coverage areas, source ecosystems, evidence burden, access boundary, and next useful move.
Create a durable campaign vault
python -B scripts/research_campaign.py init campaigns/passkeys --title "Passkey adoption decision" --query "Should small organizations adopt passkeys for customer accounts in 2026?" --tier focusedpython -B scripts/research_campaign.py validate campaigns/passkeysExpected output includes INITIALIZED and VALID. That proves an internally consistent empty campaign, not completed research.
Advance from the first unverified edge
- Record query families and actual searches.
- Ledger every retained candidate before counting inspection.
- Write a substantive source note before marking deeply read.
- Link claims to source IDs and record scope and confidence.
- Update coverage and contradictions as the field changes.
- Draft from an evidence digest and ordered section briefs.
- Assemble and structurally audit the report.
- Run a separate semantic claim review.
Expected campaign outputs
| Artifact | Purpose |
|---|---|
| Research brief and campaign.json | Inquiry, decision, scope, state, budget, blockers, and resume point. |
| Query, source, and claim ledgers | Search path, source states, claims, support, confidence, and contradictions. |
| Source notes | Full-reading evidence, method, scope, dates, limits, and useful locations. |
| Coverage and contradiction maps | What matters, what is supported, what disagrees, and which gaps remain. |
| Report and audits | Bounded synthesis, structural resolution, semantic dispositions, limits, and refresh triggers. |
Other realistic uses
Policy decision
Map statutes, guidance, empirical evidence, stakeholder incentives, competing interpretations, jurisdiction, and change triggers.
Historical investigation
Separate primary records, later scholarship, provenance disputes, missing archives, inference, and unresolved explanations.
Market or product inquiry
Distinguish vendor claims, customer evidence, public records, adoption proxies, counterexamples, and decision criteria.
Assemble and audit
python -B scripts/assemble_report.py campaigns/passkeyspython -B scripts/citation_audit.py campaigns/passkeysA passing structural audit means markers resolve to eligible records. It does not prove that each source entails the exact sentence. Use the vault reference, prompt recipes, and trust boundary for the full operating model.