Research Summarizer

Research Summarizer

Read less. Understand more. Cite correctly.

Structured research summarization workflow that turns dense source material into actionable briefs. Built for product managers, analysts, founders, and anyone who reads more than they should have to.

Not a generic "summarize this" — a repeatable framework that extracts what matters, compares across sources, and formats citations properly.

Scope — Distinct From the research/ Domain

This skill summarizes documents the user already has (papers, articles, reports pasted or attached). It performs no web search and needs no MCP server. It is NOT:

• research/litreview — academic literature discovery and review-guide generation (finds papers via Consensus/academic APIs)
• research/dossier — entity due-diligence built from live web research
• research/notebooklm — drives Google's NotebookLM product UI
• research/research — the router for open-ended "research [topic]" requests that require searching

If the user asks you to find sources rather than digest supplied ones, route to the research/ domain instead.

When This Skill Activates

Recognize these patterns from the user:

• "Summarize this paper / article / report"
• "What are the key findings in this document?"
• "Compare these sources"
• "Extract citations from this PDF"
• "Give me a research brief on [topic]"
• "Break down this whitepaper"
• Any request involving: summarize, research brief, literature review, citation, source comparison

If the user has a document and wants structured understanding → this skill applies.

Workflow

Workflow 1 — Single Source Summary

1. Identify source type

   • Academic paper → use IMRAD structure (Introduction, Methods, Results, Analysis, Discussion)
   • Web article → use claim-evidence-implication structure
   • Technical report → use executive summary structure
   • Documentation → use reference summary structure

2. Scaffold the brief — python3 scripts/format_summary.py --template academic (or article/report/executive per source type), then fill in every section from the source:

   Title: [exact title]
   Author(s): [names]
   Date: [publication date]
   Source Type: [paper | article | report | documentation]
   
   ## Key Thesis
   [1-2 sentences: the central argument or finding]
   
   ## Key Findings
   1. [Finding with supporting evidence]
   2. [Finding with supporting evidence]
   3. [Finding with supporting evidence]
   
   ## Methodology
   [How they arrived at these findings — data sources, sample size, approach]
   
   ## Limitations
   - [What the source doesn't cover or gets wrong]
   
   ## Actionable Takeaways
   - [What to do with this information]
   
   ## Notable Quotes
   > "[Direct quote]" (p. X)

3. Assess quality

   • Source credibility (peer-reviewed, reputable outlet, primary vs secondary)
   • Evidence strength (data-backed, anecdotal, theoretical)
   • Recency (when published, still relevant?)
   • Bias indicators (funding source, author affiliation, methodology gaps)

Workflow 2 — Multi-Source Comparison

1. Collect sources (2-5 documents)

2. Summarize each using the single-source workflow above

3. Build comparison matrix

   | Dimension        | Source A        | Source B        | Source C        |
   |------------------|-----------------|-----------------|-----------------|
   | Central Thesis   | ...             | ...             | ...             |
   | Methodology      | ...             | ...             | ...             |
   | Key Finding      | ...             | ...             | ...             |
   | Sample/Scope     | ...             | ...             | ...             |
   | Credibility      | High/Med/Low    | High/Med/Low    | High/Med/Low    |

4. Synthesize

   • Where do sources agree? (convergent findings = stronger signal)
   • Where do they disagree? (divergent findings = needs investigation)
   • What gaps exist across all sources?
   • What's the weight of evidence for each position?

5. Produce synthesis brief

   ## Consensus Findings
   [What most sources agree on]
   
   ## Contested Points
   [Where sources disagree, with strongest evidence for each side]
   
   ## Gaps
   [What none of the sources address]
   
   ## Recommendation
   [Based on weight of evidence, what should the reader believe/do?]

Workflow 3 — Citation Extraction

1. Run the extractor — python3 scripts/extract_citations.py document.txt --output json detects DOI/URL/author-year/numbered citations and deduplicates them
2. Review and format the extracted list in the requested style (APA 7 default); manually catch citations the regex missed
3. Classify citations by type:
   • Primary sources (original research, data)
   • Secondary sources (reviews, meta-analyses, commentary)
   • Tertiary sources (textbooks, encyclopedias)
4. Output sorted bibliography with classification tags

Supported citation formats:

• APA 7 (default) — social sciences, business
• IEEE — engineering, computer science
• Chicago — humanities, history
• Harvard — general academic
• MLA 9 — arts, humanities

Tooling

scripts/extract_citations.py

CLI utility for extracting and formatting citations from text.

Features:

• Regex-based citation detection (DOI, URL, author-year, numbered references)
• Multiple output formats (APA, IEEE, Chicago, Harvard, MLA)
• JSON export for integration with reference managers
• Deduplication of repeated citations

Usage:

# Extract citations from a file (APA format, default)
python3 scripts/extract_citations.py document.txt

# Specify format
python3 scripts/extract_citations.py document.txt --format ieee

# JSON output
python3 scripts/extract_citations.py document.txt --format apa --output json

# From stdin
cat paper.txt | python3 scripts/extract_citations.py --stdin