Literature Review Tools
Use this skill when the user asks for structured literature review work rather than only a single paper lookup.
Typical triggers:
- systematic or scoped literature review preparation
- citation cleanup before manuscript drafting
- evidence-table or evidence-matrix construction
- research-gap mapping across a paper set
- turning search results into a review-ready artifact
Environment Check
which python3 || true
python3 - <<'PY'
mods = ["pandas"]
for name in mods:
try:
__import__(name)
print(f"{name}: ok")
except Exception as exc:
print(f"{name}: missing ({exc})")
PY
For current papers, citations, or metadata that may have changed, also verify with live APIs or web search rather than relying on stale local tables.
Bundled Assets
templates/citation_table_normalize.py
templates/evidence_matrix.py
Preferred Workflow
- Gather citations first from PubMed, OpenAlex, Crossref-like exports, or existing CSV/JSON tables.
- Run
citation_table_normalize.py to normalize DOI, PMID, title, and key metadata before synthesis.
- Run
evidence_matrix.py to convert the cleaned table into a review or screening matrix.
- Only then draft a narrative synthesis, gap map, or manuscript section.
- Keep the evidence matrix and citation table as durable artifacts, not just prose.
Citation Normalization
python3 templates/citation_table_normalize.py \
--input literature/raw_hits.csv \
--title-column title \
--doi-column doi \
--pmid-column pmid \
--year-column year \
--journal-column journal \
--authors-column authors \
--output literature/normalized_citations.csv \
--summary literature/normalized_citations.json \
--bibtex-output literature/normalized_citations.bib
Use this for:
- duplicate cleanup by DOI or normalized title
- stable citation-key creation
- lightweight BibTeX export from tabular metadata
Evidence Matrix Assembly
python3 templates/evidence_matrix.py \
--input literature/normalized_citations.csv \
--title-column title \
--question-column topic \
--model-column model_system \
--intervention-column intervention \
--outcome-column outcome \
--finding-column key_finding \
--evidence-type-column study_type \
--output literature/evidence_matrix.csv \
--summary literature/evidence_matrix.json
Use this for:
- scoping reviews
- screen-ready evidence tables
- thematic synthesis inputs
- identifying under-covered mechanisms, assays, or modalities
Working Rules
- Distinguish clearly between local table cleanup and live literature search.
- Do not claim a review is systematic unless search strategy, deduplication, and inclusion logic are documented.
- Treat citation counts and publication volume as context, not proof.
- Keep exact search strings, identifiers, and date ranges when the user needs a reproducible review.
Related Skills
For paper, author, institution, trial, or public drug-database APIs, activate pharma-db-tools.
For PubMed-style biology lookups, activate bio-tools or bio-db-tools depending on the source.
For hypothesis framing, peer-review style critique, or reproducibility planning, activate scientific-workflow-tools.
1---2name: literature-review-tools3description: Research-literature workflow guide for evidence-matrix assembly, citation-table normalization, structured review synthesis, and research-gap mapping. Use when the user asks for systematic or scoped literature review workflows, citation cleanup, evidence tables, or manuscript-ready review preparation for drug-discovery and biomedical topics.4---56# Literature Review Tools78Use this skill when the user asks for structured literature review work rather than only a single paper lookup.910Typical triggers:11- systematic or scoped literature review preparation12- citation cleanup before manuscript drafting13- evidence-table or evidence-matrix construction14- research-gap mapping across a paper set15- turning search results into a review-ready artifact1617## Environment Check1819```bash20which python3 || true21python3 - <<'PY'22mods = ["pandas"]23for name in mods:24 try:25 __import__(name)26 print(f"{name}: ok")27 except Exception as exc:28 print(f"{name}: missing ({exc})")29PY30```3132For current papers, citations, or metadata that may have changed, also verify with live APIs or web search rather than relying on stale local tables.3334## Bundled Assets3536- `templates/citation_table_normalize.py`37- `templates/evidence_matrix.py`3839## Preferred Workflow40411. Gather citations first from PubMed, OpenAlex, Crossref-like exports, or existing CSV/JSON tables.422. Run `citation_table_normalize.py` to normalize DOI, PMID, title, and key metadata before synthesis.433. Run `evidence_matrix.py` to convert the cleaned table into a review or screening matrix.444. Only then draft a narrative synthesis, gap map, or manuscript section.455. Keep the evidence matrix and citation table as durable artifacts, not just prose.4647## Citation Normalization4849```bash50python3 templates/citation_table_normalize.py \51 --input literature/raw_hits.csv \52 --title-column title \53 --doi-column doi \54 --pmid-column pmid \55 --year-column year \56 --journal-column journal \57 --authors-column authors \58 --output literature/normalized_citations.csv \59 --summary literature/normalized_citations.json \60 --bibtex-output literature/normalized_citations.bib61```6263Use this for:64- duplicate cleanup by DOI or normalized title65- stable citation-key creation66- lightweight BibTeX export from tabular metadata6768## Evidence Matrix Assembly6970```bash71python3 templates/evidence_matrix.py \72 --input literature/normalized_citations.csv \73 --title-column title \74 --question-column topic \75 --model-column model_system \76 --intervention-column intervention \77 --outcome-column outcome \78 --finding-column key_finding \79 --evidence-type-column study_type \80 --output literature/evidence_matrix.csv \81 --summary literature/evidence_matrix.json82```8384Use this for:85- scoping reviews86- screen-ready evidence tables87- thematic synthesis inputs88- identifying under-covered mechanisms, assays, or modalities8990## Working Rules9192- Distinguish clearly between local table cleanup and live literature search.93- Do not claim a review is systematic unless search strategy, deduplication, and inclusion logic are documented.94- Treat citation counts and publication volume as context, not proof.95- Keep exact search strings, identifiers, and date ranges when the user needs a reproducible review.9697## Related Skills9899For paper, author, institution, trial, or public drug-database APIs, activate `pharma-db-tools`.100For PubMed-style biology lookups, activate `bio-tools` or `bio-db-tools` depending on the source.101For hypothesis framing, peer-review style critique, or reproducibility planning, activate `scientific-workflow-tools`.