Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
A direct command skips the review prompt. Inspect the source before running it.
Deep literature review — PubMed, EuropePMC, bioRxiv preprints, citation networks, evidence synthesis. Disambiguates queries, runs collision-aware searches, grades evidence T1-T4, and produces structured reports. Use for systematic literature review, meta-analysis evidence collection, and detailed answer-with-citations workflows.
Literature Deep Research
Systematic literature research: disambiguate, search with collision-aware queries, grade evidence, produce structured reports.
KEY PRINCIPLES: (1) Disambiguate first (2) Right-size deliverable (3) Grade every claim T1-T4 (4) All sections mandatory even if "limited evidence" (5) Source attribution for every claim (6) English-first queries, respond in user's language (7) Report = deliverable, not search log
LOOK UP, DON'T GUESS
Search PubMed/EuropePMC FIRST before reasoning. A published paper beats memory.
No results -> BROADEN (remove most restrictive term)
Too many -> NARROW (add specific terms)
Answer usually in abstract of top results
Failed query -> try DIFFERENT TERMS/synonyms, don't repeat
COMPUTE, DON'T DESCRIBE
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
Check first 20 results. If >20% off-topic, build negative filter: NOT [collision1] NOT [collision2].
Gene family: "ADAR" NOT "ADAR2" NOT "ADARB1". Cross-domain: add context terms.
1.7 Compound Queries (e.g., "metformin in breast cancer")
Resolve both entities, then cross-reference via CTD_get_chemical_gene_interactions, CTD_get_chemical_diseases, OpenTargets drug-target/drug-disease tools. Intersect shared targets/pathways.
1.8 General Academic / 1.9 Interdisciplinary
Non-bio: skip bio tools, use ArXiv/DBLP/OSF. Cross-domain: resolve bio entities with 1.1-1.3, search CS/general in parallel, merge and cross-reference.
Phase 2: Literature Search
Methodology stays internal. Report shows findings, not process.
2.1 Query Strategy
Step 1: Seeds (15-30 core papers): domain-specific title searches with date/sort filters.
Step 2: Citation expansion: PubMed_get_cited_by, EuropePMC_get_citations/references, PubMed_get_related, SemanticScholar_get_recommendations, OpenCitations_get_citationsStep 3: Collision-filtered broader queries: "[TERM]" AND ([context]) NOT [collision]
2.2 Literature Tools — core set + adaptive by domain
Run the core multi-field set on every review (catches what any single index misses), then add the domain rows that match the subject. Don't fire every source blindly — 6–10 well-chosen indexes beat 20 noisy ones.
ALWAYS run (core, all disciplines): PubMed_search_articles, EuropePMC_search_articles, openalex_search_works (query param search/query) oropenalex_literature_search (query param search_keywords) — pick one and match its param; mixing them silently returns off-topic results — and SemanticScholar_search_papers
Multi-source: advanced_literature_search_agent (12+ DBs; needs Azure key -- fallback: query the core set individually).
Citation impact: iCite_search_publications (RCR/APT), iCite_get_publications (by PMID), scite_get_tallies (support/contradict). PubMed-only; for CS use SemanticScholar.
A domain-specific index returning 0 (e.g. ArXiv on a pure-clinical topic) is normal — only worry if the whole core set is empty.
2.3-2.4 Full-Text & PubMed Zero-Result Fallback
Full-text: see FULLTEXT_STRATEGY.md for three-tier strategy.
CRITICAL: PubMed returns 0 for ~30% of valid queries. Always retry with EuropePMC when PubMed returns empty. This is not optional.
2.5 Tool Failure / OA Handling
Retry once -> fallback tool. Key fallbacks: PubMed_get_cited_by -> EuropePMC_get_citations -> OpenCitations. OA: Unpaywall if configured, else Europe PMC/PMC/OpenAlex flags.
Phase 3: Evidence Grading
Tier
Label
Bio Example
CS/ML Example
T1
Mechanistic
CRISPR KO + rescue, RCT
Formal proof, controlled ablation
T2
Functional
siRNA knockdown phenotype
Benchmark with baselines
T3
Association
GWAS, screen hit
Observational, case study
T4
Mention
Review article
Survey, workshop abstract
Inline: Target X regulates Y [T1: PMID:12345678]. Per theme: summarize evidence distribution.
Report Output
File
Mode
[topic]_report.md
Full
[topic]_factcheck_report.md
Factoid
[topic]_bibliography.json + .csv
All
Progressive update: create report with all section headers immediately. Fill after each phase. Write Executive Summary LAST.
Use 15-section template from REPORT_TEMPLATE.md. Domain adaptations: bio (architecture/expression/GO/disease), drug (properties/MOA/PK/safety), disease (epi/patho/genes/treatments), general (history/theories/evidence/applications).
Communication
Brief progress updates only: "Resolving identifiers...", "Building paper set...", "Grading evidence..."
Do NOT expose: raw tool outputs, dedup counts, search round details.
References
TOOL_NAMES_REFERENCE.md -- 123 tools with parameters
