find_evidence
Fact-check or substantiate a claim against the corpus. Given a textual claim, retrieves and CLASSIFIES evidence into supporting / contradicting / neutral groups. Uses HyDE (hypothetical document expansion) — server generates plausible supporting/contradicting text, embeds, retrieves, then ranks by relation to original claim. Returns chunks with selfContained flag (safe-to-cite indicator). Use for fact-verification, controversy mapping, 'is this claim known?' queries. Modes: 'fast' (~3s, symmetric-by-construction grouping) / 'deep' (~10s, independent NLI classification). IMPORTANT: in 'fast' mode the supporting/contradicting counts are approximately balanced BY CONSTRUCTION and do NOT reflect actual literature distribution. Use 'deep' when measuring controversy balance, literature distribution, or any claim of the form 'the field is split N:M on this'.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | 'fast' (~3s): retrieval uses symmetric HyDE pools — top-20 chunks against the supporting-hypothetical plus top-20 against the contradicting-hypothetical, then each chunk is assigned to the bucket whose HyDE-vector it scored higher against. Because the retrieval pool is symmetric and the classification mirrors the retrieval direction, supporting/contradicting counts come out approximately balanced regardless of the actual distribution of evidence in the corpus (a topic that is 90% supported in the literature will still show a ~1:1 split here). Use fast mode for 'is there evidence on either side?', not for 'how is the field actually split?'. May also misclassify chunks that mention the topic but logically point the other way (e.g. a paper explaining 'BN is bad in transformers' may land in the contradicting bucket for an 'LN > BN' claim). 'deep' (~10s): adds an independent per-chunk LLM NLI classification on top of the union pool, so counts reflect actual semantic distribution and can be arbitrarily asymmetric. Use 'deep' whenever classification accuracy or distribution shape matters — including controversy mapping and any analysis that interprets the supporting/contradicting ratio as a signal about the field. | fast |
| claim | Yes | Statement to fact-check or substantiate | |
| limit | No | Max results PER group (supporting/contradicting/neutral) | |
| detail | No | standard | |
| run_id | No | Optional. The active methodist run_id (as returned by the methodist diagnose / get_current_dose door). Pass it whenever you call this tool while working inside a run, so the call is attributed to that run for the §8 usage crosscheck — attribution is run-anchored, so it stays correct even if your access token refreshes mid-run. Must be YOUR run: a run_id owned by a different principal, or a non-existent run_id, is rejected. | |
| categories | No | ||
| selfContainedOnly | No | If true, only return chunks marked as understandable without prior context (safer to cite) |