Literature Review

A structured literature-review skill grounded in PRISMA-style protocols (adapted for non-medical fields), source-assessment frameworks, and thematic synthesis patterns.

When to use this skill

• Conducting a systematic literature review on a specific question
• Building a research bibliography for a paper, report, or grant
• Performing a scoping review to map a field
• Auditing an existing review for gaps, bias, or methodological flaws
• Synthesizing findings from a structured set of sources
• Preparing a research-grounded section of a longer report

Inputs the advisor expects

• Research question(s) — specific, answerable
• Inclusion / exclusion criteria
• Time bound (e.g., past 5 years)
• Geographic / domain bound
• Source types accepted (peer-reviewed, gray literature, conference)
• Existing seed sources (if any)

Clarify First

Before building the review, settle the inputs below. When one is missing or vague and would change the result, ask about it; when it wouldn't, use a sensible default and say which one you used.

• Research question (PICO frame): makes search and synthesis tractable; vague questions yield unfocused reviews.
• Review type (systematic, scoping, or narrative): sets rigor, criteria stringency, and output structure (e.g. whether a PRISMA flow is needed).
• Inclusion / exclusion criteria (year range, source type, methodology): drives screening and reproducibility.
• Synthesis goal (answer a specific question vs map a field): selects the synthesis approach.

Ask about the two or three inputs that matter most for this request, not the whole list. If the user wants a result straight away, produce it and state your assumptions at the top.

Workflows

Workflow 1 — Plan and execute the search

1. Refine the research question (PICO / PEO format works).
2. Run search_strategy_builder.py against the question + criteria to produce a search strategy (database list, queries, filters).
3. Execute searches; capture results.

python3 litreview/scripts/search_strategy_builder.py \
  --input question.json --format markdown

Workflow 2 — Score source quality and relevance

1. Capture each source with metadata (authors, date, venue, methodology).
2. Run source_quality_scorer.py to grade each on 6 quality dimensions
   • relevance to question.
3. Triage: include / exclude / read-in-full.

python3 litreview/scripts/source_quality_scorer.py \
  --input sources.json --format markdown

Workflow 3 — Synthesize findings into themes

1. Tag each source with themes + key findings.
2. Run thematic_synthesis_builder.py to cluster sources by theme, surface evidence strength, identify gaps.

python3 litreview/scripts/thematic_synthesis_builder.py \
  --input tagged_sources.json --format markdown

Decision frameworks

Search strategy — the PICO frame

• Population / problem
• Intervention / phenomenon of interest
• Comparator (if relevant)
• Outcome

A well-framed question makes search and synthesis tractable.

Inclusion / exclusion criteria

• Year range
• Language
• Source type (peer-reviewed, gray, conference, preprint)
• Methodology (empirical, theoretical, review)
• Geographic scope
• Quality threshold

Publish criteria up front; apply consistently.

Source quality dimensions

Dimension	Question
Methodology	Is the method sound?
Sample / dataset	Is it adequate for the claim?
Peer review	Has it been peer-reviewed?
Reproducibility	Is data / code available?
Recency	Is it current?
Citation impact	Has it been cited / accepted?

A single sub-dimension is rarely fatal; the combination matters.

Synthesis approaches

Approach	When
Narrative synthesis	Heterogeneous sources; explanatory
Thematic synthesis	Multiple sources address common themes
Meta-analysis	Quantitative, comparable studies
Realist synthesis	Complex interventions; context-mechanism-outcome
Scoping review	Mapping a field rather than answering specific question

For most non-clinical fields, thematic synthesis is the default.

Common engagements

"Help me build the literature review for my paper"

1. Frame the research question (PICO).
2. Define inclusion criteria.
3. Identify search databases / repositories.
4. Execute searches; deduplicate.
5. Screen titles + abstracts; full-text the candidates.
6. Tag and synthesize.
7. Write: gaps, themes, my contribution.

"Audit my draft literature review"

1. Check the search strategy: reproducible? comprehensive?
2. Check inclusion criteria: applied consistently?
3. Check synthesis: themes substantiated?
4. Check gap identification: real gaps, or convenient?
5. Check citation balance: not over-relying on a single source / group.

"Map the landscape of [research area]"

1. Conduct a scoping review (different from systematic).
2. Less stringent quality criteria; broader scope.
3. Goal: map the field, not answer specific question.
4. Output: themes, gaps, key authors, key venues.

Anti-patterns to avoid

• Search strategy that's "Google Scholar for keywords." Not reproducible.
• Inclusion criteria written after seeing results. Cherry-picking.
• Synthesizing only confirming sources. Bias.
• Citing without reading. Cite chains repeat errors.
• No quality scoring. All sources weighted equally.
• No gap discussion. Reader can't see what's not known.
• Over-reliance on one author / group / venue. Hidden bias.
• No PRISMA-style flow diagram (for systematic reviews). Process opaque.

Scope & Limitations

In Scope:

• Search strategies from a PICO-style question with search_strategy_builder.py: Boolean query strings per database, filters and a PRISMA-style log template
• Source scoring on six quality dimensions (methodology, sample, peer review, reproducibility, recency, citation impact) plus relevance with source_quality_scorer.py, triaged to include, exclude or read in full
• Theme-by-source evidence tables with thematic_synthesis_builder.py, showing well-supported, contested and gap themes
• Guidance on inclusion criteria, PRISMA discipline adapted for non-medical fields, and choosing among narrative, thematic, scoping and other synthesis approaches

Out of Scope:

• Running the searches and retrieving full texts. The user executes the queries in each database.
• Meta-analysis statistics and effect-size pooling (see data-analytics/statistical-analyst/ for general statistics)
• Patent prior-art searching (see research/patent/)
• Writing grant proposals that build on the review (see research/grants/)

Important Caveats:

• The tools have no database access. Source metadata, theme tags and findings are entered by the user, and quality scores are heuristics built from that metadata.
• The output is not a registered systematic review protocol. Pre-registration, dual independent screening and a formal risk-of-bias tool are steps the user must do separately.
• Database syntax and coverage change over time, so generated queries need testing in each database before use.

References

• references/search-strategy-and-prisma.md — search patterns, PRISMA discipline
• references/source-quality-assessment.md — quality dimensions, common assessments
• references/synthesis-and-citation-management.md — synthesis approaches, citation hygiene

Related skills

• research/grants — grant proposals built on literature
• research/patent — IP-focused literature search
• research/dossier — intelligence research patterns
• product-team/research-summarizer — synthesizing qualitative research