research-summarizer
Structured research summarization agent skill for non-dev users. Handles academic papers, web articles, reports, and documentation. Extracts key findings, generates comparative analyses, and produces properly formatted citations. Use when: user wants to summarize a research paper, compare multiple sources, extract citations from documents, or create structured research briefs. Plugin for Claude Code, Codex, Gemini CLI, and OpenClaw.
- License 许可
- MIT
- 最近更新
- 2026-06-04
- Stars
- ★ 2
- Forks
- 0
01 前言 Front Matter
- name
- research-summarizer
- license
- MIT
- metadata
- { "author": "Alireza Rezvani", "updated": 1773619200000, "version": "1.0.0", "category": "product" }
- description
- Structured research summarization agent skill for non-dev users. Handles academic papers, web articles, reports, and documentation. Extracts key findings, generates comparative analyses, and produces properly formatted citations. Use when: user wants to summarize a research paper, compare multiple sources, extract citations from documents, or create structured research briefs. Plugin for Claude Code, Codex, Gemini CLI, and OpenClaw.
02 资源文件 4
- 参考文档references/citation-formats.md3.2 KB
- 参考文档references/summary-templates.md4.0 KB
- 脚本scripts/extract_citations.py9.5 KB
- 脚本scripts/format_summary.py10.6 KB
03 SKILL.md 正文
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.
Slash Commands
| Command | What it does |
|---|---|
/research:summarize |
Summarize a single source into a structured brief |
/research:compare |
Compare 2-5 sources side-by-side with synthesis |
/research:cite |
Extract and format all citations from a document |
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
/research:summarize — Single Source Summary
-
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
-
Extract structured brief
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) -
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)
/research:compare — Multi-Source Comparison
-
Collect sources (2-5 documents)
-
Summarize each using the single-source workflow above
-
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 | -
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?
-
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?]
/research:cite — Citation Extraction
- Scan document for all references, footnotes, in-text citations
- Extract and format using the requested style (APA 7 default)
- Classify citations by type:
- Primary sources (original research, data)
- Secondary sources (reviews, meta-analyses, commentary)
- Tertiary sources (textbooks, encyclopedias)
- 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
scripts/format_summary.py
CLI utility for generating structured research summaries.
Features:
- Multiple summary templates (academic, article, report, executive)
- Configurable output length (brief, standard, detailed)
- Markdown and plain text output
- Key findings extraction with evidence tagging
Usage:
# Generate structured summary template
python3 scripts/format_summary.py --template academic
# Brief executive summary format
python3 scripts/format_summary.py --template executive --length brief
# All templates listed
python3 scripts/format_summary.py --list-templates
# JSON output
python3 scripts/format_summary.py --template article --output json
Quality Assessment Framework
Rate every source on four dimensions:
| Dimension | High | Medium | Low |
|---|---|---|---|
| Credibility | Peer-reviewed, established author | Reputable outlet, known author | Blog, unknown author, no review |
| Evidence | Large sample, rigorous method | Moderate data, sound approach | Anecdotal, no data, opinion |
| Recency | Published within 2 years | 2-5 years old | 5+ years, may be outdated |
| Objectivity | No conflicts, balanced view | Minor affiliations disclosed | Funded by interested party, one-sided |
Overall Rating:
- 4 Highs = Strong source — cite with confidence
- 2+ Mediums = Adequate source — cite with caveats
- 2+ Lows = Weak source — verify independently before citing
Summary Templates
See references/summary-templates.md for:
- Academic paper summary template (IMRAD)
- Web article summary template (claim-evidence-implication)
- Technical report template (executive summary)
- Comparative analysis template (matrix + synthesis)
- Literature review template (thematic organization)
See references/citation-formats.md for:
- APA 7 formatting rules and examples
- IEEE formatting rules and examples
- Chicago, Harvard, MLA quick reference
Proactive Triggers
Flag these without being asked:
- Source has no date → Note it. Undated sources lose credibility points.
- Source contradicts other sources → Highlight the contradiction explicitly. Don't paper over disagreements.
- Source is behind a paywall → Note limited access. Suggest alternatives if known.
- User provides only one source for a compare → Ask for at least one more. Comparison needs 2+.
- Citations are incomplete → Flag missing fields (year, author, title). Don't invent metadata.
- Source is 5+ years old in a fast-moving field → Warn about potential obsolescence.
Installation
One-liner (any tool)
git clone https://github.com/alirezarezvani/claude-skills.git
cp -r claude-skills/product-team/research-summarizer ~/.claude/skills/
Multi-tool install
./scripts/convert.sh --skill research-summarizer --tool codex|gemini|cursor|windsurf|openclaw
OpenClaw
clawhub install cs-research-summarizer
Related Skills
- product-analytics — Quantitative analysis. Complementary — use research-summarizer for qualitative sources, product-analytics for metrics.
- competitive-teardown — Competitive research. Complementary — use research-summarizer for individual source analysis, competitive-teardown for market landscape.
- content-production — Content writing. Research-summarizer feeds content-production — summarize sources first, then write.
- product-discovery — Discovery frameworks. Complementary — research-summarizer for desk research, product-discovery for user research.
04 同仓库更多 Skills
syllabus
Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Triggers whenever a user uploads a syllabus, course outline, or curriculum document and wants supplementary readings. Also triggers on: 'syllabus reading list', 'find papers for my course', 'create a reading list from this syllabus', 'recent research for my class', 'supplementary readings', 'find journal articles for these topics', 'what recent papers cover this material', 'any new research on these course topics', 'update my syllabus with recent papers'. Even casual mentions when a syllabus is attached should trigger this skill.
research
Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Triggers — "research [topic]", "look into [topic]", "what do we know about [topic]", "investigate [topic]", "find me information on [topic]", "do some research on [topic]", "I need to understand [topic]", or any research request that doesn't obviously match a more-specific specialist skill. Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log.
pulse
Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Triggers: 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]', or any variation requesting multi-source recency intelligence on a topic. Also use for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.
patent
Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Triggers: 'prior art search for [invention]', 'patent search on [topic]', 'freedom to operate analysis', 'FTO for [product]', 'patent landscape for [field]', 'is [invention] novel', 'patents on [topic]', 'competitive patent analysis', 'prior art for litigation', 'patent diligence on [company]'. Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.
notebooklm
Browser automation skill for controlling Google's NotebookLM. Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio Overview, infographics, slide decks, study guides, briefing docs, mind maps, timelines, FAQs), and creating new notebooks. Triggers on any phrase involving NotebookLM — 'open NotebookLM', 'check my [name] notebook', 'pull info from NotebookLM', 'ask my notebook about X', 'add [source] to NotebookLM', 'create an infographic in NotebookLM', 'use NotebookLM Studio', 'generate a slide deck from my notebook', or any variation where the goal involves NotebookLM. Requires browser automation environment — fails gracefully when unavailable.
litreview
Academic literature orientation skill that searches papers via Consensus, builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a professionally formatted Word document (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — not a finished review, but an orientation guide that lets a researcher dive in confidently. Triggers: 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'. Do NOT trigger for single one-off paper searches where the user just wants a quick list — that's a plain Consensus search.