Literature Research Protocol

Purpose

Conduct comprehensive literature research on the manuscript topic and generate a structured summary of:

•Background context and foundations
•Related work and competing approaches
•Recent advances and state-of-the-art
•Gaps that the manuscript addresses

Prerequisites

Best if you have:

•manuscript_plan.md (outline with research questions)
•Draft manuscript sections (especially Introduction/Methods)
•references.bib (existing citations to build upon)

Minimum requirement:

•PROJECT.md with clear research topic and key findings

Workflow

Phase 1: Topic Extraction

•
Read Context Documents:
- •Read PROJECT.md to understand the research domain
- •Read manuscript_plan.md if available (for detailed topics)
- •Read manuscript/introduction.md or manuscript/abstract.md if available
- •Read references.bib to see what's already cited
•
Extract Key Research Topics:
- •Primary methodology (e.g., "transformer-based protein structure prediction")
- •Domain area (e.g., "computational biology", "deep learning")
- •Specific techniques (e.g., "attention mechanisms", "MSA features")
- •Comparison methods (e.g., "AlphaFold2", "RoseTTAFold")
•
Formulate Search Queries: Create 3-5 targeted search queries combining:
- •Core method + domain
- •Technique + application
- •"Recent advances in [topic]"
- •"State of the art [domain]"
- •Each competing method mentioned

Phase 2: Literature Search

Use WebSearch tool to find:

•
Foundational Papers (highly cited, >1000 citations)
- •Query: "[core method] review" OR "[domain] survey"
- •Focus on papers from last 5 years for reviews, last 10 for foundations
•
Recent Advances (last 2 years, 2024-2026)
- •Query: "[method] 2024" OR "[method] 2025" OR "[method] 2026"
- •Look for: NeurIPS, ICLR, ICML, Nature, Science papers
•
Direct Competitors (methods you're comparing against)
- •Query: exact names of competing methods
- •Find their original papers and recent improvements
•
Application Domain (specific to your problem)
- •Query: "[your application] + [your method type]"
- •Example: "protein structure prediction transformers"

For each relevant paper found:

•Extract: Authors, Title, Venue, Year, DOI (critical!)
•Note: Key contribution, methodology, results
•Record: Citation key format (e.g., author2024)
•Capture direct quote: Extract 1-2 sentences that best represent the key finding or contribution

Phase 3: Synthesis

Generate a structured summary in manuscript/literature.md:

markdown

# Literature Review: [Manuscript Topic]

**Generated:** [Date]
**Based on:** [manuscript_plan.md / PROJECT.md]

## 1. Background & Foundations (200-300 words)

### Core Concepts
- [Topic 1]: Foundational work by [Author et al., Year]. Key insight: ...
- [Topic 2]: Established by [Author et al., Year]. Approach: ...

### Historical Context
- Evolution from [old method] to [current method]
- Major breakthrough: [cite landmark paper]

## 2. Related Work (300-400 words)

### Approach A: [Method Name]
- **Key Papers**: [Author1, Year], [Author2, Year]
- **Methodology**: [Brief description]
- **Strengths**: ...
- **Limitations**: ...

### Approach B: [Method Name]
- **Key Papers**: [Author3, Year], [Author4, Year]
- **Methodology**: [Brief description]
- **Strengths**: ...
- **Limitations**: ...

### Approach C: [Method Name]
- **Key Papers**: [Author5, Year]
- **Methodology**: [Brief description]
- **Strengths**: ...
- **Limitations**: ...

## 3. Recent Advances (200-300 words)

### State-of-the-Art
- [Recent Paper 1, 2024/2025]: Achieved [result]. Method: ...
- [Recent Paper 2, 2024/2025]: Novel approach using ...

### Current Trends
- Trend 1: [Description]
- Trend 2: [Description]

## 4. Research Gaps (100-150 words)

**Identified Gaps:**
1. [Gap 1 that your work addresses]
2. [Gap 2 that your work addresses]
3. [Gap 3 that your work addresses]

**How Our Work Fits:**
[Brief statement of how your manuscript fills these gaps]

## 5. Key Citations to Add

**Essential references to cite in manuscript:**

### Background (Introduction)
- [author2020]: Foundational work on [topic]
- [author2021]: Comprehensive review of [domain]

### Related Work (Methods/Discussion)
- [author2023]: Competing approach [Method A]
- [author2024]: Recent improvement to [Method B]
- [author2025]: State-of-the-art baseline

### Recent Comparisons (Results/Discussion)
- [author2024a]: Benchmark dataset
- [author2024b]: Performance comparison

## 6. Citation Integration Guide

**Where to cite what:**

**Introduction:**
- Cite [author2020, author2021] when introducing the problem
- Cite [author2023] when discussing prior approaches

**Methods:**
- Cite [author2022] when describing your architecture basis
- Cite [author2023] when contrasting with existing methods

**Results:**
- Cite [author2024a, author2024b] when presenting comparisons

**Discussion:**
- Cite [author2025] when positioning your work

---

## References to Add to references.bib

[Provide properly formatted BibTeX entries for all cited works]

Phase 4: Citation File Generation

Create or update bib_additions.bib with BibTeX entries for all newly found papers:

bibtex

@article{author2024,
  title={Title of Paper},
  author={Author, First and Author, Second},
  journal={Journal/Conference},
  year={2024},
  doi={10.1234/journal.2024.12345},
  url={https://doi.org/10.1234/journal.2024.12345}
}

CRITICAL: Always include DOI when available. DOIs are permanent identifiers and essential for verification.

Phase 5: Evidence Documentation

Create literature_evidence.csv with columns:

csv

doi,citation_key,evidence
10.1038/s41586-021-03819-2,jumper2021,"We developed AlphaFold, a deep learning system that predicts protein structures with atomic accuracy even in cases in which no similar structure is known."
10.1126/science.abj8754,baek2021,"RoseTTAFold can generate accurate models of protein structures and complexes using as input only a protein sequence."
10.1093/bioinformatics/bty1057,author2024,"Our approach achieves 15% improvement over existing methods while reducing computational cost by 3-fold."

Requirements for evidence quotes:

•Extract 1-2 sentences that capture the KEY finding or contribution
•Use direct quotes (verbatim from the paper)
•Focus on quantitative results or novel methodological claims
•Ensure quote is self-contained and understandable
•Include page number in comment if possible

Output Files

Generate three files in the manuscript/ directory (per schema: schemas/manuscript.yaml):

•
manuscript/literature.md
- •One-page structured summary (800-1000 words)
- •Organized by themes, not chronologically
- •Includes citation keys in [author2024] format
- •Each citation includes DOI: e.g., [jumper2021, DOI:10.1038/...]
- •Required sections: Background, Related Work, Recent Advances, Research Gaps
•
manuscript/literature_citations.bib
- •BibTeX entries for all newly found references
- •Must include DOI field for each entry
- •Ready to append to existing references.bib
•
manuscript/literature_evidence.csv
- •Three columns: doi, citation_key, evidence
- •Direct quotes from each cited paper
- •Enables verification and evidence chains
- •Can be used to check claims against original sources

Validation

After generating files, validate the literature review:

bash

python scripts/rrwrite-validate-manuscript.py --file manuscript/literature.md --type literature

State Update

After successful validation, update workflow state:

python

import sys
from pathlib import Path
sys.path.insert(0, str(Path('scripts').resolve()))
from rrwrite_state_manager import StateManager

manager = StateManager()
# Count papers from literature_citations.bib
import re
with open('manuscript/literature_citations.bib', 'r') as f:
    papers_found = len(re.findall(r'^@\w+{', f.read(), re.MULTILINE))

manager.update_workflow_stage("research", status="completed",
                              file_path="manuscript/literature.md",
                              papers_found=papers_found)

Display updated progress:

bash

python scripts/rrwrite-status.py

If validation passes, confirm completion and show progress. If it fails, fix issues and re-validate.

Quality Criteria

Ensure the literature review:

•✅ Covers foundational work (pre-2020)
•✅ Includes recent advances (2024-2026)
•✅ Identifies all major competing approaches
•✅ Explains relationships between methods
•✅ Highlights gaps your work addresses
•✅ Provides actionable integration guidance
•✅ All citations are real and verifiable
•✅ BibTeX entries are properly formatted
•✅ DOIs included for all papers (when available)
•✅ Evidence quotes captured for verification
•✅ literature_evidence.csv created with direct quotes

Search Strategy Notes

Coverage targets:

•15-25 papers total
•3-5 foundational/review papers
•5-8 directly related work papers
•4-6 recent advances (last 2 years)
•2-4 competing method papers

Quality indicators for papers:

•Published in top-tier venues (Nature, Science, NeurIPS, ICML, ICLR)
•High citation count (>50 for recent, >500 for foundational)
•Relevant to your specific approach and domain
•Provides reproducible benchmarks or datasets

Verification:

•Cross-check papers exist via multiple sources
•Prioritize papers with DOIs (permanent identifiers)
•Accept arXiv IDs for preprints (format: arXiv:YYMM.NNNNN)
•Verify author names and publication years
•Confirm venue/journal names are correct
•Extract direct quote from abstract or key results section
•Record quote in evidence file for later verification

Integration with Drafting

After generating the literature review:

•
Update Introduction:
- •Integrate background citations from Section 1
- •Add related work references from Section 2
•
Update Methods:
- •Add citations justifying methodological choices
- •Reference papers you're building upon or modifying
•
Update Discussion:
- •Compare your results to recent state-of-the-art
- •Position your work in context of current trends
•
Inform Future Work:
- •Cite papers suggesting future directions
- •Reference emerging techniques to try

Example Usage

code

User: "Use /rrwrite-research-literature to research the background for my protein structure prediction paper"

Agent:
1. Reads PROJECT.md and manuscript_plan.md
2. Extracts topics: "transformer architecture", "protein folding", "AlphaFold2", "attention mechanisms"
3. Searches for:
   - "protein structure prediction review 2024"
   - "transformer protein folding"
   - "AlphaFold2 improvements 2024"
   - "attention mechanisms structural biology"
4. Finds 20 relevant papers with DOIs
5. Extracts direct quotes from each paper
6. Generates:
   - literature_review.md (structured summary, 950 words)
   - bib_additions.bib (20 BibTeX entries with DOIs)
   - literature_evidence.csv (20 rows with DOIs and quotes)
   - literature_integration_notes.md
7. Provides integration guidance

Output: "✓ Literature review complete. Found 20 relevant papers (5 foundational, 8 related work, 7 recent). Generated manuscript/literature.md (950 words), manuscript/literature_citations.bib (20 entries with DOIs), and manuscript/literature_evidence.csv (20 evidence quotes)."

Evidence File Example

literature_evidence.csv:

csv

doi,citation_key,evidence
10.1038/s41586-021-03819-2,jumper2021,"We developed AlphaFold, a deep learning system that predicts protein structures with atomic accuracy even in cases in which no similar structure is known. AlphaFold achieved a median accuracy of 92.4 GDT on CASP14 targets."
10.1126/science.abj8754,baek2021,"RoseTTAFold can generate accurate models of protein structures and complexes using as input only a protein sequence. The method achieves accuracy comparable to AlphaFold while being more computationally efficient."
10.1038/s41467-024-12345-6,yang2024,"We demonstrate that pre-trained protein language models can reduce MSA requirements by 80% while maintaining prediction accuracy above 85% on CASP15 targets."
arXiv:2401.12345,zhang2025,"Our efficient transformer architecture achieves real-time protein structure prediction (< 1 second per protein) with only 5% accuracy loss compared to AlphaFold2."

Using the evidence file:

•Cross-reference claims in your manuscript with direct quotes
•Verify that your interpretation aligns with original sources
•Provide evidence for peer reviewers if challenged
•Enable reproducible claim verification

Limitations & Handling

If no manuscript outline exists:

•Use PROJECT.md "Key Findings" to infer topics
•Focus on broader domain literature
•Request user clarification on specific sub-topics

If references.bib already extensive:

•Compare found papers with existing citations
•Flag papers that should be added
•Suggest papers that might be outdated or less relevant

If topic is very niche:

•Expand search to broader domain
•Include methodological foundations even if not domain-specific
•Flag if insufficient literature found (suggest broadening)

Notes

•DO NOT hallucinate papers - Only cite papers found via WebSearch or in references.bib
•Verify all citations - Double-check author names, years, venues
•Always capture DOIs - Essential for permanent identification and verification
•Extract exact quotes - Copy verbatim from paper abstract or results, no paraphrasing
•Be selective - Quality over quantity; cite only the most relevant papers
•Stay current - Prioritize papers from last 2-3 years for "Recent Advances"
•Cross-reference - If a paper cites another relevant paper, follow the trail
•Use WebFetch if needed - To read paper abstracts and extract accurate quotes
•Format evidence properly - Ensure CSV is properly escaped (quotes within quotes)