Skill: roboticresults/deep-researcher-ai (version 1.0.0)

--- name: deep-researcher description: "Generate comprehensive 30-40 page academic research papers with full citations. Trigger: deep research, generate research paper, academic paper, literature review, research report, 30-40 page paper, comprehensive analysis, full citations, scholarly work." metadata: builtin_skill_version: "1.1" openclaw_native: true replaces: knowledge-digest triggers: - "deep research" - "generate research paper" - "academic paper" - "literature review" - "research report" - "comprehensive analysis" - "scholarly paper" - "long research paper" - "research paper 30 pages" - "full citations research" --- # Deep Researcher — Academic Research Paper Generator Generate comprehensive, academic-grade research papers (30-40 pages) with 40-80 unique citations, following a rigorous 7-stage workflow. Adapts to any field — AI, medicine, economics, social sciences, engineering, and more. ## Workflow Overview ``` STAGE 1: Topic Analysis → Decompose topic into sub-questions STAGE 2: Source Discovery → Query academic & industry databases STAGE 3: Content Synthesis → Extract, summarize, map source relationships STAGE 4: Cross-Verification → Triangulate claims, verify facts STAGE 5: Content Expansion → Fill gaps, add case studies, data STAGE 6: Synthesis & Writing → Assemble paper chapter-by-chapter STAGE 7: Refinement & QA → Polish, format citations, validate ``` --- ## Stage 1: Topic Analysis Decompose the research topic into 12-15 subtopics. Identify: - Primary research questions - Scope boundaries (time period, geography, industry) - Feasibility for 30-40 page scope - Key theories and seminal works to anchor the paper **Output**: Topic Deconstruction Report with subtopics, research questions, and knowledge gaps. --- ## Stage 2: Source Discovery Query multiple source categories using OpenClaw's native tools: | Category | Sources | Tool | |----------|---------|------| | Academic | arXiv, Google Scholar, PubMed, Semantic Scholar | `batch_web_search` | | Economic | World Bank API, IMF, OECD Stats | `batch_web_search` | | Industry | McKinsey Insights, Statista, Gartner | `batch_web_search` + `extract_content_from_websites` | | Code/AI | GitHub, Hugging Face, arXiv (CS) | `batch_web_search` | | News | Reuters, BBC, RSS feeds | `batch_web_search` | | Patents | Google Patents | `batch_web_search` | **Tool**: `batch_web_search` (up to 10 concurrent queries) For each search, extract: title, authors, year, DOI/URL, abstract, key findings. **Output**: 40-80 candidate sources organized by category and relevance. --- ## Stage 3: Content Synthesis For each major source: - Extract core contribution, methodology, key findings (3-5 bullet points), limitations - Group by theme, methodology, and chapter alignment - Identify patterns: recurring themes, contradictions, gaps **Output**: Synthesized source notes (150-200 words per source), cross-reference map, draft literature review. --- ## Stage 4: Cross-Verification - Every factual claim must be backed by ≥1 source - Critical claims (statistics, dates, specific findings) verified against 2-3 independent sources - Flag sources with potential bias or industry funding - Identify underrepresented perspectives **Output**: Verification log, triangulation matrix, bias assessment. --- ## Stage 5: Content Expansion - Search for case studies, historical precedents, comparative analyses - Add quantitative data from World Bank, IMF, OECD where relevant - Include expert viewpoints, industry reports, conference proceedings - Aim for 15-20 distinct subtopics covered **Output**: Expanded source list (+10-20 sources), comparative analysis, historical timeline. --- ## Stage 6: Synthesis & Writing Assemble the paper using the **Standard Research Paper Structure** below. Integrate citations in APA 7th format. Write 15,000-18,000 words targeting 30-40 pages. ### Standard Research Paper Structure ``` 1. Title Page (clear title, keywords, date) 2. Abstract (300-500 words, 3-5 keywords) 3. Executive Summary (1-2 pages, key takeaways for decision-makers) 4. Chapter 1: Introduction (3-4 pages) - Background & context - Problem statement - Research objectives & questions - Significance & scope 5. Chapter 2: Literature Review (6-8 pages) - Theoretical framework - Key themes (organized thematically) - Major studies & seminal works - Gaps in existing research 6. Chapter 3: Methodology (4-5 pages) - Research design (qualitative/quantitative/mixed) - Data sources & search strategy - Inclusion/exclusion criteria - Analysis techniques & AI tools used 7. Chapter 4: Data Collection (3-4 pages) - Sample/data description - Collection procedures - Ethical considerations 8. Chapter 5: Analysis & Findings (8-10 pages) - Descriptive findings - Quantitative/qualitative results - Comparative and longitudinal analysis - Visual elements (tables, figures) 9. Chapter 6: Discussion (3-4 pages) - Interpretation of key findings - Theoretical & practical implications - Limitations & counterarguments 10. Chapter 7: Conclusion (2-3 pages) - Summary of contributions - Actionable recommendations - Future research directions 11. References (5-8 pages, 40-80 sources) 12. Appendices (optional) ``` **Citation style**: APA 7th Edition (Author, Year) — default. Also supports MLA 9th and Chicago Notes/Bibliography. --- ## Stage 7: Refinement & QA Run the quality checklist: ### Accuracy - [ ] 0% hallucinated claims — every claim backed by ≥1 source - [ ] All statistics cross-checked against primary sources - [ ] All dates within ±1 day of source - [ ] All DOIs resolve correctly ### Completeness - [ ] 30-40 page target (15,000-18,000 words) - [ ] ≥40 unique citations - [ ] 15-20 distinct subtopics covered - [ ] All 7 chapters present - [ ] 5+ figures/tables ### Coverage - [ ] 4+ different source types (academic, industry, news, government) - [ ] 70%+ sources from last 5 years - [ ] 3+ distinct viewpoints represented - [ ] At least 1 counterargument documented ### Citation Integrity - [ ] All in-text citations appear in References - [ ] All References have in-text citations - [ ] No orphan URLs - [ ] APA 7th formatting consistent throughout ### Literary Quality - [ ] Formal academic tone, no slang - [ ] Third-person perspective - [ ] Clear transitions between chapters - [ ] No repetition or redundancy - [ ] Consistent terminology **Output**: Final polished paper + QA report --- ## Output Formats | Format | Description | Tool | |--------|-------------|------| | **Markdown** | Default, editable | Direct output | | **PDF** | Academic submission | `minimax-pdf` skill | | **DOCX** | Word processing | `minimax-docx` skill | Request with: `"[topic] — output as PDF"` or `"[topic] — output as DOCX"` --- ## APA 7th Citation Quick Reference **In-text**: `(Author, Year)` or `Author (Year) showed that...` **Reference entry (Journal)**: ``` Author, A. A., & Author, B. B. (Year). Title of article. Journal Name, Volume(Issue), Page.Range. https://doi.org/xxxxx ``` **Reference entry (Book)**: ``` Author, A. A. (Year). Title of book (Edition ed.). Publisher. ``` **Reference entry (Web)**: ``` Author, A. A. (Year, Month Day). Title of page. Website Name. https://url ``` --- ## Citation Density Rule Target: ≥1 citation per 150-200 words across the full paper. This ensures every claim is evidence-backed and academically rigorous. --- ## Source Priority Matrix | Priority | Source Types | Cost | |----------|-------------|------| | **HIGH** | arXiv, PubMed, World Bank, IMF, OECD, Hugging Face, GitHub | Free | | **MEDIUM** | Google Scholar, IEEE, McKinsey, Gartner, Statista | Free/Premium | | **LOW** | News feeds, Twitter, Reddit, news blogs | Free | Always prioritize free, authoritative, open-access sources first. --- ## Data Sources Registry ### Academic - **arXiv**: `https://export.arxiv.org/api/query` — cutting-edge AI/ML/theory, no API key - **Google Scholar**: `batch_web_search` — comprehensive peer-reviewed coverage - **PubMed/PMC**: `https://eutils.ncbi.nlm.nih.gov/entrez/eutils/` — biomedical, life sciences - **Semantic Scholar**: `https://api.semanticscholar.org/` — CS academic sources ### Economic & Policy - **World Bank**: `https://api.worldbank.org/v2/` — free, no key required - **IMF**: `https://api.imf.org/` — macroeconomic data - **OECD**: `https://stats.oecd.org/` — comparative policy data ### Technology & AI - **Hugging Face**: `https://api.huggingface.co/` — ML models, datasets, papers - **GitHub API**: `https://api.github.com/` — code trends, repositories - **Google Patents**: `https://patents.google.com/` — innovation trends ### Industry - **McKinsey Insights**: Public articles and reports - **Gartner**: Industry analysis (subscription) - **Statista**: Statistics and market data (subscription) --- ## Troubleshooting | Issue | Solution | |-------|----------| | "Insufficient sources" | Expand keyword list; use Boolean operators (AND/OR/NOT); try alternative databases | | "Page count too short" | Expand Stage 5 (content expansion); add case studies, comparative data, visual elements | | "Citation gaps" | Return to Stage 2; search for missing angles; add industry reports and government data | | "Hallucination risk" | Always verify facts via Cross-Verification stage; cite primary sources only | | "Formatting inconsistent" | Run APA 7th reference check; ensure all in-text citations match reference list | --- ## Iteration Triggers - **From Stage 4 → Stage 3**: Cross-verification reveals hallucination or insufficient evidence - **From Stage 5 → Stage 2**: Expansion search finds critical gaps in core coverage - **From Stage 6 → Stage 4**: Writing reveals missing critical sources - **Page count <30**: Expand Stage 5, then revisit Stage 6 --- ## Integration Notes This skill replaces and significantly extends the `knowledge-digest` skill's research capabilities. Where knowledge-digest focuses on learning materials from existing documents, deep-researcher generates original academic research from primary and secondary sources across multiple databases. Both skills can coexist — use `deep-researcher` for original paper creation, `knowledge-digest` for study aids from existing materials.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)