---
id: literature-review
description: Structured scientific review with thematic synthesis and citations
version: 3
contexts: paper-set,library-corpus
activation: auto
match: /\b(literature review|lit review|review of (the )?literature)\b/i
match: /\b(conduct|write|create|generate|draft)\b.*\b(review|synthesis|survey)\b.*\b(on|about|regarding|of)\b/i
match: /\bconduct a literature review\b/i
match: /\b(review|synthesize|survey)\b.*\b(research|papers?|studies|findings?|literature)\b/i
---

<!--
  SKILL: Literature Review

  This skill activates when you ask for a literature review or synthesis
  (e.g., "conduct a literature review on X", "synthesize the research").

  You can customize:
  - Discovery phase: change how papers are found and selected
  - Review structure: modify sections (intro, themes, gaps, conclusion)
  - Citation format: adjust citation style
  - Depth vs breadth: change how many papers are deep-read vs skimmed

  Your changes are preserved across plugin updates.
  To reset to default, delete this file — it will be recreated on next restart.
-->

## Literature Review — structured scientific review workflow

When the user asks for a literature review, follow this three-phase workflow. The goal is a well-structured scientific review with inline citations, thematic synthesis, and identified research gaps.

### Phase 1 — Paper Discovery (1-2 tool calls)

Identify the corpus of papers to review:

- **Papers already in context**: If the user has pinned or selected papers (visible in `selectedPaperContexts` or `fullTextPaperContexts`), use those directly. No discovery step needed.
- **Topic search**: If the user provides a topic or keywords and wants evidence from their Zotero library, use `library_retrieve({ query:'<topic>', queryVariants:[...], intent:'enumerate', depth:'metadata'|'evidence' })` to search metadata/abstracts/indexed text broadly when translation, acronyms, notation variants, or terminology equivalents would improve recall. Use `intent:'summarize', depth:'evidence'` for method or theme taxonomies.
- **Collection**: If the user names a collection, use `library_search({ entity:'collections', mode:'search', text:'<collection name>' })` to resolve it, then `library_retrieve({ scope:{ collectionIds:[<collectionId>] }, query:'<review topic>', queryVariants:[...], intent:'enumerate', depth:'metadata'|'evidence' })` when variants would help. Use `intent:'summarize'` for collection-grounded taxonomies.
- **Whole library**: If the user wants a review across their entire library, use `zotero_script({ mode:'read', description:'Summarize candidate papers for a literature review', script:'...' })` to aggregate candidates in Zotero's runtime (same pattern as `library-analysis`).

Cap the corpus at **15-20 papers**. If more match, select the most relevant based on title/abstract relevance to the topic. Use `library_read` to retrieve metadata (title, authors, year, abstract, publicationTitle) for all discovered papers.

### Phase 2 — Selective Deep Reading (2-5 tool calls)

Do **NOT** read every paper in full. Abstracts from Phase 1 are sufficient for most.

Deep-read only the **3-5 most relevant papers** to the review topic. If `library_retrieve` already returned good evidence snippets, use those before calling `paper_read`.

1. Use `paper_read({ mode:'overview', targets:[...] })` for selected papers.
2. For targeted claims: `paper_read({ mode:'targeted', query:'...', targets:[...] })` with focused questions (e.g., "What methods were used?", "What were the key findings?").
3. Use `paper_read({ mode:'figures', query:'...' })` only when figures are directly relevant; reserve `mode:'visual'` for explicit page/layout inspection.

Prioritize breadth over depth — it is better to include 15 papers with abstract-level understanding than 5 papers with full-text reads.

When deep-reading papers with MinerU cache, note any key figures (result plots, comparison tables, architecture diagrams). Consider including select figures in the final review when they illustrate important findings that are hard to convey with text alone.

### Phase 3 — Synthesis and Writing

Write the review directly in the chat response. Use this structure:

1. **Introduction** (1-2 paragraphs)
   - State the review topic and its significance
   - Describe the scope: how many papers, what time range, what databases/collections

2. **Thematic Sections** (2-4 sections)
   - Group papers by theme, methodology, or approach — **never** list papers one by one
   - Each section should synthesize findings across multiple papers
   - Use inline citations: `(Author, Year)` format, e.g., `(Smith et al., 2023)`
   - Highlight agreements, contradictions, and methodological differences

3. **Research Gaps and Future Directions** (1 paragraph)
   - Identify what is missing from the reviewed literature
   - Suggest directions for future research

4. **Conclusion** (1 paragraph)
   - Summarize the key takeaways

5. **References**
   - List all cited papers in alphabetical order
   - Format: `Author(s). (Year). Title. *Journal*, Volume(Issue), Pages.`

If key figures from deep-read papers would strengthen a thematic point, first call `paper_read({ mode:'figures', query:'<figure request>' })` and embed the extracted PDF crop paths it returns.
Treat `paper_read({ mode:'figures' })` as the authority for figure crop cache reuse/regeneration.
Use its returned crop paths/artifacts as-is and do not inspect or validate `figure_crops` metadata before analysis or writing.
Place figures within the thematic sections they relate to, not in a separate section.
Do not embed MinerU source image paths.

### Citation rules

- Use citations and short quotes to make important paper-specific claims checkable, not to decorate every paragraph.
  Cite concrete claims about methods, datasets, results, definitions, equations, limitations, and the authors' own interpretations.
  Use short direct quotes when the exact wording matters or when a key point benefits from visible evidence.
  For background explanation, synthesis, or your own interpretation, write clearly and cite only the specific paper claim it depends on.
  Do not append a standalone source label or citation-only final line after ordinary summary prose; source labels on their own line belong only after direct blockquotes when no quote anchor is available.
  Use quote anchors only for direct article evidence; do not use them for publication metadata, DOI links, journal names, or source labels alone.
  Prefer a readable answer with traceable evidence over repetitive citations or low-information quotes.
- Use `(Author, Year)` for single-author papers, `(Author & Author, Year)` for two, `(Author et al., Year)` for three or more.
- The citation label should match the Zotero item metadata (use `creators` and `date` fields).
- Do NOT invent citations or cite papers not in the user's library.
- If a deep-read passage provides a quote anchor like `[[quote:Q_x7a2]]`, use that anchor token for the direct quote. Direct quote text must be copied verbatim in the original source language; never translate quote text to match the user's language. Put any translation outside the blockquote as explanation. If no quote anchor is provided, put the source label on the next non-empty line after the blockquote.
- Do not write `[[source=...]]`, `section=...`, or `chunk=...` metadata in the final answer.

### After writing

- Ask the user if they want the review saved as a Zotero note: `note_write({ mode:'create', content:'...', target:'standalone' })`.
- If saving, convert the markdown to the Zotero note HTML format.

### Key rules

- Budget: aim for **3-6 tool calls** total across all phases. Prefer one `library_retrieve` call over many `paper_read` calls for broad collection/library search.
- Preserve coverage wording from `library_retrieve`: sampled snippets support evidence summaries, but only complete metadata/indexed/searchable-text coverage can support exhaustive folder-level claims. Use `paperMatches` before manually inferring from snippets.
- Do NOT dump all paper content into context — use abstracts first, deep-read selectively.
- Do NOT produce a per-paper summary list — synthesize thematically.
- If the review covers >10 papers, prioritize breadth (abstracts) over depth (full reads).
- If fewer than 3 papers match the topic, tell the user and offer to search online with `literature_search`.
