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skills/competitive-pipeline/references/evidence-research.md
4.34 KB · Oct 5, 2026 · 18:26 UTC
# Evidence Research Procedure
Gather evidence for one scoped biopharma question. Return the findings in the format requested by the user, with supporting sources and explicit gaps.
## Your Output Contract
Return structured research notes with:
- the scoped topic you investigated
- findings / claims
- `evidence_rating` for each claim
- `citations` with canonical `source_ref` objects and verbatim `quote`
- explicit `gaps` for anything not supported strongly enough
Use plain Markdown and readable source links. Keep canonical source references with the claims so they can be traced to the documents read.
## Evidence Rules
1. Prefer Maven Bio MCP tools over ad hoc web search.
2. Use document retrieval when a claim needs evidence:
- `search_documents`
- `read_document`
- `get_recent_events`
3. `read_document` must use actual tool-returned document IDs, NCT IDs, or URLs. Do not invent or shorten IDs.
4. Treat discovery tools as scaffolding, not proof:
- `search_entities`
- `research_landscape`
- `fetch_related`
- `get_financials` (public-market financial statements: revenue, EBITDA, market cap, cash flow, analyst ratings)
- `get_financings` (private/round-level capital activity: rounds the company received or invested in, by recipient, investor, type, value, date)
- `get_deals` (cross-company BD transactions: licensing, M&A, R&D collaborations, JVs, by party + role, deal type, value, date)
- When reasoning about a company's runway or capital position, pull both. `aspects=["financials", "financings"]` on `research_entity` returns them in a single call. On every financing row, `value_status` disambiguates `total_value_usd`: `"unconfirmed"` means Maven's data does not have the amount, not that the round was undisclosed in the world.
- When a research question touches drug approvals, label content, exclusivity, patents, designations, or LOE timing, anchor the answer in primary sources via `search_documents` with `source_types=["fda_filings"]` and then `read_document`, rather than a summary. Cite the document and its date for any label-sourced claim.
5. For any landscape, pipeline, benchmark, or other master analysis, do not stop after discovery. After you establish the baseline universe, run a document augmentation pass to look for missing entities, recent updates, contradictions, and stronger support for high-impact claims.
6. `Direct Evidence` requires that the source was actually read in this session.
7. If strong evidence is unavailable, mark the claim accordingly instead of stretching the source.
## Fallback Ladders
### If entity resolution fails
- retry with the raw entity name only
- move sponsor/company/disambiguating text into the optional context hint
- use `match_entity` for canonical single-entity lookup
- use `search_entities` only when you need a broader candidate set by criteria
- preserve ambiguity explicitly if the entity still cannot be resolved cleanly
### If a tool times out
- retry once with narrower scope
- reduce batch size
- narrow by source type, entity scope, or claim-specific wording
### If host web fetch is blocked
- stop retrying blocked host fetches repeatedly
- use `search_documents` to locate Maven-indexed or near-equivalent content
- use `read_document` on the returned ID, NCT, or URL
- if that still fails, preserve the gap explicitly
## Suggested Output Shape
```json
{
"topic": "Example topic",
"claims": [
{
"claim": "Exampledrug reported 93.8% ORR in the named cohort.",
"evidence_rating": "Direct Evidence",
"citations": [
{
"source_ref": {
"id": "doc_abc123",
"kind": "document",
"tool": "read_document",
"url": "https://example.com/doc"
},
"quote": "NPM1m ORR 93.8%"
}
],
"notes": []
}
],
"gaps": []
}
```
## Fail-Closed Behavior
If evidence is missing:
- do not guess
- do not cite entity lookup results as if they were documents
- do not fabricate quotes
Instead, record the unresolved question in `gaps` and explain what was searched.
## Master Analysis Reminder
If your task is to help build a master analysis:
- start with structured MCP tools to define the baseline universe
- then augment with document search and targeted reads
- then reconcile the final claim set
Do not assume the first structured result set is complete enough to finalize the analysis.
SHA-256: a7e29bc5af5096b1ab02be4d32ae59031c6312c20ee910cd5104fe52309fcdd4