drugclaw/literature-review-tools

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

1. Gather citations first from PubMed, OpenAlex, Crossref-like exports, or existing CSV/JSON tables.
2. Run citation_table_normalize.py to normalize DOI, PMID, title, and key metadata before synthesis.
3. Run evidence_matrix.py to convert the cleaned table into a review or screening matrix.
4. Only then draft a narrative synthesis, gap map, or manuscript section.
5. 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.