Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Literature review for academic and R&D research: search strategy, source assessment, synthesis, and citation management. Use when conducting a systematic literature review, building a bibliography, or preparing a research-grounded report.
.claude/skills/borghei-litreview/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-05 | ✗→✓ | ▲ Improved | 19% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 15% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 13% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 16% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 104% | 0% |
A structured literature-review skill grounded in PRISMA-style protocols (adapted for non-medical fields), source-assessment frameworks, and thematic synthesis patterns.
Before building the review, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
search_strategy_builder.py against the question + criteria toproduce a search strategy (database list, queries, filters).
bashpython3 litreview/scripts/search_strategy_builder.py \ --input question.json --format markdown
source_quality_scorer.py to grade each on 6 quality dimensions+ relevance to question.
bashpython3 litreview/scripts/source_quality_scorer.py \ --input sources.json --format markdown
thematic_synthesis_builder.py to cluster sources by theme,surface evidence strength, identify gaps.
bashpython3 litreview/scripts/thematic_synthesis_builder.py \ --input tagged_sources.json --format markdown
A well-framed question makes search and synthesis tractable.
Publish criteria up front; apply consistently.
| 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.
| 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.
references/search-strategy-and-prisma.md — search patterns, PRISMA disciplinereferences/source-quality-assessment.md — quality dimensions, common assessmentsreferences/synthesis-and-citation-management.md — synthesis approaches, citation hygieneresearch/grants — grant proposals built on literatureresearch/patent — IP-focused literature searchresearch/dossier — intelligence research patternsproduct-team/research-summarizer — synthesizing qualitative research| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 17,054 | 18,337 | +8% | 1 | 1 | 0% | 3,117 | 4,679 | +50% | 0 | 0 | — |
case-02 | fail→fail | 19,853 | 20,108 | +1% | 1 | 1 | 0% | 3,116 | 4,460 | +43% | 0 | 0 | — |
case-03 | pass→pass | 25,840 | 31,672 | +23% | 1 | 1 | 0% | 4,264 | 6,683 | +57% | 0 | 0 | — |
case-04 | pass→pass | 9,848 | 8,732 | -11% | 1 | 1 | 0% | 1,792 | 2,935 | +64% | 0 | 0 | — |
case-05 | fail→pass | 8,653 | 2,073 | -76% | 1 | 1 | 0% | 1,506 | 1,798 | +19% | 0 | 0 | — |
case-06 | fail→pass | 9,447 | 2,341 | -75% | 1 | 1 | 0% | 1,601 | 1,839 | +15% | 0 | 0 | — |
case-07 | fail→pass | 21,829 | 2,923 | -87% | 1 | 1 | 0% | 1,690 | 1,906 | +13% | 0 | 0 | — |
case-08 | pass→pass | 13,131 | 11,453 | -13% | 1 | 1 | 0% | 2,111 | 3,178 | +51% | 0 | 0 | — |
case-09 | fail→pass | 11,923 | 4,704 | -61% | 1 | 1 | 0% | 1,947 | 2,254 | +16% | 0 | 0 | — |
case-10 | fail→pass | 15,102 | 20,348 | +35% | 1 | 1 | 0% | 2,193 | 4,466 | +104% | 0 | 0 | — |
case-11 | fail→fail | 15,346 | 18,206 | +19% | 1 | 1 | 0% | 2,340 | 4,354 | +86% | 0 | 0 | — |
case-12 | pass→pass | 12,140 | 6,573 | -46% | 1 | 1 | 0% | 1,860 | 2,490 | +34% | 0 | 0 | — |
case-13 | pass→pass | 11,631 | 13,043 | +12% | 1 | 1 | 0% | 1,867 | 3,560 | +91% | 0 | 0 | — |
case-14 | pass→pass | 12,971 | 9,759 | -25% | 1 | 1 | 0% | 1,893 | 2,807 | +48% | 0 | 0 | — |
case-15 | pass→pass | 7,468 | 6,827 | -9% | 1 | 1 | 0% | 1,296 | 2,524 | +95% | 0 | 0 | — |
case-16 | pass→pass | 11,877 | 12,531 | +6% | 1 | 1 | 0% | 1,851 | 3,302 | +78% | 0 | 0 | — |
case-17 | pass→pass | 12,711 | 8,138 | -36% | 1 | 1 | 0% | 2,166 | 2,879 | +33% | 0 | 0 | — |
case-18 | fail→pass | 11,714 | 1,714 | -85% | 1 | 1 | 0% | 1,791 | 1,735 | -3% | 0 | 0 | — |
case-19 | fail→pass | 9,293 | 2,138 | -77% | 1 | 1 | 0% | 1,390 | 1,696 | +22% | 0 | 0 | — |
case-20 | fail→fail | 15,014 | 21,713 | +45% | 1 | 1 | 0% | 2,516 | 5,115 | +103% | 0 | 0 | — |
case-21 | fail→fail | 18,057 | 21,639 | +20% | 1 | 1 | 0% | 3,595 | 5,814 | +62% | 0 | 0 | — |
case-22 | fail→fail | 10,724 | 6,778 | -37% | 1 | 1 | 0% | 1,599 | 2,514 | +57% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +32 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.