Research Lookup

Compile the external evidence needed to plan and write a high-quality scientific manuscript. The default academic workflow targets 60 verified, unique references and produces a manuscript-ready research packet rather than a loose list of links. Here verified_references counts successful retrieval of nonempty Extract excerpts, excluding flagged retractions. It does not establish bibliographic identity, claim support, peer review, or absence of corrections; those require source review.

Scope and boundaries

Use this skill when the user explicitly wants:

• literature and background research for a manuscript
• many high-quality academic references
• evidence supporting or contradicting a scientific claim
• a structured evidence matrix or claim-to-source map
• current studies, methods precedent, mechanisms, limitations, or research gaps

Do not activate it for casual factual questions that do not need research, private or unpublished material, or a claim that can be answered from user-provided files. Query text is sent to Parallel. It is sent to OpenRouter only when Perplexity is explicitly selected or the user enables that fallback.

This skill compiles external evidence. It cannot supply the user's unpublished study data, decide what their Results show, or guarantee systematic-review completeness. For a PRISMA-style systematic review, use literature-review for protocols, database-specific searching, screening, exclusion reasons, and risk of bias.

Parallel-first routing

Important compatibility behavior:

• A bare script query uses Parallel Search. Chat Completions remains available only through explicit backend selection.
• --force-backend parallel remains an alias for explicit Parallel Research.
• Academic keywords select the multi-pass Parallel academic strategy; they do not silently switch the provider to Perplexity.
• --batch, --json, -o/--output, the ResearchLookup class, progress output, and the existing result envelope remain supported.

Recommended manuscript workflow

1. Capture manuscript context

Use the user's available context to constrain retrieval:

• research question or hypothesis
• study type
• population or biological/technical system
• intervention or exposure
• comparator
• outcomes
• field and date range
• target journal, if known

The script accepts a JSON object through --context-file. Do not invent missing study details. A bare topic is supported, but the packet will flag its section briefs as broad.

Example:

{
  "research_question": "How does intervention X affect outcome Y?",
  "study_type": "prospective cohort",
  "population": "adults with condition Z",
  "exposure": "intervention X",
  "comparator": "standard care",
  "outcomes": ["primary outcome Y", "adverse events"],
  "field": "clinical epidemiology",
  "target_journal": "Journal Name"
}

2. Run the academic evidence pipeline

From the repository root (illustrative paid-service run; review its scope first):

python skills/research-lookup/scripts/research_lookup.py \
  "Evidence relevant to the manuscript's research question" \
  --academic \
  --target-references 60 \
  --context-file manuscript-context.json \
  --packet-dir sources/manuscript-research \
  --json

The academic pipeline runs bounded advanced Search passes for:

1. recent peer-reviewed primary studies
2. systematic reviews, meta-analyses, and consensus evidence
3. seminal and foundational publications
4. methods, protocols, validation, benchmarks, and mechanisms
5. contradictory, null, negative, replication, and limitation evidence
6. an unrestricted companion search when filtered passes do not reach the target

It prioritizes PubMed/PMC, Europe PMC, Crossref, OpenAlex, Semantic Scholar, arXiv/bioRxiv/medRxiv, major journals, and authoritative institutional sources. Domain filters are not treated as exhaustive; the companion pass reduces blind spots.

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