Literature Synthesis

You help sociologists move from a corpus of papers to a deep understanding of a field. This is the analytical bridge between finding papers (lit-search) and writing about them (argument-builder).

Project Integration

This skill reads from project.yaml when available:

# From project.yaml
paths:
  lit_synthesis: literature/synthesis/

Project type: This skill works for all project types. Literature synthesis is essential for qualitative, quantitative, and mixed methods research.

Updates progress.yaml when complete:

status:
  lit_synthesis: done
artifacts:
  field_synthesis: literature/synthesis/field-synthesis.md
  theoretical_map: literature/synthesis/theoretical-map.md
  debate_map: literature/synthesis/debate-map.md

The Lit Trilogy

This skill is the middle step in a three-skill workflow:

Input: Papers in Zotero (imported from lit-search or user's existing library) Output: Organized understanding of the field ready for writing

When to Use This Skill

Use this skill when users:

• Have a corpus of papers (from lit-search or their own collection)
• Need to understand the theoretical landscape before writing
• Want to identify debates, tensions, and competing positions
• Need to organize papers thematically or by theoretical tradition
• Want deep reading notes, not just metadata extraction

Core Principles

1. Read deeply, not widely: Better to understand 15 papers thoroughly than 50 superficially.

2. Theoretical traditions matter: Papers exist within intellectual lineages. Map who cites whom and why.

3. Debates are gold: Competing positions create space for contributions. Find the tensions.

4. Organization serves writing: The clusters and maps you create should directly feed argument-builder's architecture phase.

5. Full text when possible: Abstracts tell you what; full text tells you how and why.

Reading Modes

Phase 1 (Deep Reading) supports two modes for accessing paper content:

Choose based on your situation:

• Zotero mode: When papers are in your library and you've already highlighted key passages
• Docling mode: When processing many new PDFs quickly, or when Zotero isn't set up

Both modes produce the same structured reading notes with required identifiers.

Zotero Integration

For Zotero mode, this skill uses the bundled zotero and zotero-rag skills:

Setup

See mcp/zotero-setup.md for detailed configuration.

Two Complementary Skills

Key Capabilities

zotero skill (structured access):

• search_items - Find papers by keyword, author, tag
• get_item - Retrieve full metadata
• collection_items - List items in a collection

zotero-rag skill (semantic search):

• semantic_search - Find passages by conceptual similarity
• get_chunk_context - Expand results with surrounding text
• find_similar_chunks - Discover related discussions across documents

Workflow Integration

1. From lit-search: Import the BibTeX export into Zotero
2. Acquire PDFs: Use Zotero's "Find Available PDF" or manual download
3. Index for RAG: Run index_library collection_key="YOUR_COLLECTION"
4. Read and annotate: Highlight key passages, add notes
5. lit-synthesis reads: Access via zotero tools and semantic search via zotero-rag

Docling PDF Conversion

For Docling mode, PDFs are converted to markdown for agent-based reading:

Setup

Install docling:

pip install docling

Using reading-agent Skill

For structured reading notes, use the bundled reading-agent skill:

/reading-agent

Paper: [Author Year - Title]
PDF: /path/to/paper.pdf
DOI: [doi]

The reading-agent skill handles PDF conversion and produces structured notes with:

• Bibliographic info and identifiers
• Core arguments and theoretical frameworks
• Methods and empirical strategy
• Key findings and contribution claims
• Key quotes with page numbers

Batch Processing

For batch processing many papers:

1. Convert PDFs: Run scripts/pdf-to-md.sh on each paper
2. Use reading-agent in batch mode:

   /reading-agent
   
   Batch process these papers:
   - /papers/smith2020.pdf (DOI: 10.1086/123456)
   - /papers/jones2019.pdf (OpenAlex: W2123456789)
   

3. Collect outputs: Notes saved to reading-notes/ directory

Conversion Scripts (Alternative)

Located in scripts/ directory:

Workflow Phases

Phase 0: Corpus Audit

Goal: Assess what's in the corpus and identify gaps.

Process:

• Review the database from lit-search (or user's Zotero collection)
• Count papers by year, journal, author, theoretical tradition
• Identify potential gaps in coverage
• Prioritize which papers need deep reading vs. skimming

Output: corpus-audit.md with statistics and reading priorities.

Pause: User confirms corpus coverage and reading priorities.

Phase 1: Deep Reading

Goal: Close read priority papers and extract analytical insights.

Process:

• For each priority paper, read full text via Zotero MCP
• Extract: argument structure, theoretical framework, key concepts, methodological approach
• Note: how theory is deployed, what evidence supports claims, limitations acknowledged
• Create structured reading notes

Output: reading-notes/ directory with per-paper notes.

Pause: User reviews reading notes for key papers.

Phase 2: Theoretical Mapping

Goal: Identify intellectual traditions and lineages.

Process:

• Identify which theoretical frameworks appear across papers
• Map citation relationships (who cites whom)
• Note foundational texts and their descendants
• Identify "camps" or schools of thought
• Document key concepts and how they're used

Output: theoretical-map.md with traditions, key theorists, and concept definitions.

Pause: User reviews theoretical landscape.

Phase 3: Thematic Clustering

Goal: Organize papers by what they study and how.

Process:

• Group papers by empirical focus (population, setting, phenomenon)
• Group papers by theoretical approach
• Group papers by methodological strategy
• Identify papers that bridge multiple clusters
• Note within-cluster consensus and variation

Output: thematic-clusters.md with organized paper groupings.

Pause: User reviews clustering logic.

Phase 4: Debate Mapping

Goal: Identify tensions, disagreements, and competing positions.

Process:

• Find explicit disagreements (papers that critique each other)
• Find implicit tensions (contradictory findings or incompatible assumptions)
• Identify unresolved questions the field is grappling with
• Note where evidence is mixed or contested
• Document the "state of the debate" for each tension

Output: debate-map.md with positions, evidence, and unresolved questions.

Pause: User reviews debates and selects focus areas.

Phase 5: Field Synthesis

Goal: Create comprehensive understanding ready for writing.

Process:

• Synthesize across phases into coherent field understanding
• Identify the most productive gaps for contribution
• Recommend which argument-builder cluster (Gap-Filler, Theory-Extender, etc.) fits
• Create the handoff document for argument-builder

Output: field-synthesis.md with integrated understanding and writing recommendations.

Output Files

lit-synthesis/
├── corpus-audit.md           # Phase 0: What's in the corpus
├── reading-notes/            # Phase 1: Per-paper notes
│   ├── smith2020-cultural-frames.md    # Filename: author-year-short-title
│   ├── jones2019-institutional.md
│   └── ...                             # Each file has identifier frontmatter
├── theoretical-map.md        # Phase 2: Traditions and lineages
├── thematic-clusters.md      # Phase 3: Paper groupings
├── debate-map.md             # Phase 4: Tensions and positions
└── field-synthesis.md        # Phase 5: Integrated understanding

Note: Filenames use author-year-short-title.md for human readability, but the frontmatter identifiers (OpenAlex ID, DOI, Zotero key) are the authoritative way to match notes back to source papers.

Reading Note Template

For each paper in Phase 1, notes must include identifier frontmatter to enable reliable retrieval across the workflow:

---
# Required: At least one unique identifier
openalex_id: W2123456789    # From lit-search database (preferred)
doi: 10.1086/123456         # Digital Object Identifier
zotero_key: ABC123XY        # Zotero item key (if in library)

# Recommended: Additional metadata for filtering
first_author: Smith
year: 2020
short_title: cultural-frames
---

# Smith 2020 - Cultural Frames

## Bibliographic Info
- Full citation: [from Zotero or database]
- DOI: [link]
- OpenAlex: https://openalex.org/W2123456789

## Core Argument
[1-2 sentences: What is the paper arguing?]

## Theoretical Framework
- Tradition: [e.g., Bourdieusian, institutionalist, interactionist]
- Key concepts used: [list]
- How theory is deployed: [description vs. extension vs. critique]

## Empirical Strategy
- Data: [what kind]
- Methods: [how analyzed]
- Sample: [who/what]

## Key Findings
1. [Finding 1]
2. [Finding 2]
3. [Finding 3]

## Contribution Claim
[What does the paper claim to contribute?]

## Limitations (as noted by authors)
- [Limitation 1]
- [Limitation 2]

## My Notes
[Your analytical observations, connections to other papers, questions raised]

## Key Quotes
> "[Quote 1]" (p. X)

> "[Quote 2]" (p. Y)

## Tags
[theoretical-tradition] [empirical-focus] [method] [relevant-to-my-project]

Model Recommendations

Phase 1 model choice: Use Opus for close reading of key theoretical papers; use Haiku via docling mode for processing larger batches where structured extraction is the goal.

Starting the Synthesis

When the user is ready to begin:

1. Identify the corpus:

   "Where are your papers? A Zotero collection? A folder of PDFs? A database from lit-search? How many papers total?"

2. Choose reading mode:

   "For Phase 1, we have two options:

   • Zotero mode: Best if papers are in your library with annotations. Uses Opus for deep reading.
   • Docling mode: Best for batch-processing PDFs. Converts to markdown and uses Haiku agents. Which fits your situation?"

3. Verify setup (based on mode):

   • Zotero: Check MCP is configured (see mcp/zotero-setup.md)
   • Docling: Verify docling is installed (pip install docling)

4. Set priorities:

   "Which papers are most central to your project? We'll deep-read those first and skim the rest."

5. Clarify goals:

   "What are you trying to understand about this field? Are you looking for gaps, debates, or a specific theoretical tradition?"

6. Proceed with Phase 0 to audit the corpus.

Key Reminders

• Identifiers are essential: Every reading note must have at least one unique identifier (OpenAlex ID, DOI, or Zotero key) in its frontmatter
• Choose the right mode: Zotero mode for annotated papers; Docling mode for batch processing
• Annotations accelerate: If you've already highlighted papers, Zotero mode leverages that work
• Quality over quantity: Deep reading 15 papers beats skimming 50
• Debates are opportunities: Every tension you find is a potential contribution space
• This feeds argument-builder: The outputs here become inputs there—keep that handoff in mind