--- name: research-lookup description: Look up current research information using parallel-cli search (primary, fast web search), the Parallel Chat API (deep research), or Perplexity sonar-pro-search (academic paper searches). Automatically routes queries to the best backend. Use for finding papers, gathering research data, and verifying scientific information. allowed-tools: Read Write Edit Bash license: MIT license compatibility: parallel-cli required (primary); PARALLEL_API_KEY and OPENROUTER_API_KEY optional for deep/academic backends metadata: skill-author: K-Dense Inc. --- # Research Information Lookup ## Overview This skill provides real-time research information lookup with **intelligent backend routing**: - **parallel-cli search** (parallel-web skill): **Primary and default backend** for all research queries. Fast, cost-effective web search with academic source prioritization. Uses `parallel-cli search` with `--include-domains` for scholarly sources. - **Parallel Chat API** (`core` model): Secondary backend for complex, multi-source deep research requiring extended synthesis (60s-5min latency). Use only when explicitly needed. - **Perplexity sonar-pro-search** (via OpenRouter): Used only for academic-specific paper searches where scholarly database access is critical. The skill automatically detects query type and routes to the optimal backend. ## When to Use This Skill Use this skill when you need: - **Current Research Information**: Latest studies, papers, and findings - **Literature Verification**: Check facts, statistics, or claims against current research - **Background Research**: Gather context and supporting evidence for scientific writing - **Citation Sources**: Find relevant papers and studies to cite - **Technical Documentation**: Look up specifications, protocols, or methodologies - **Market/Industry Data**: Current statistics, trends, competitive intelligence - **Recent Developments**: Emerging trends, breakthroughs, announcements ## Visual Enhancement with Scientific Schematics **When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.** If your document does not already contain schematics or diagrams: - Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams - Simply describe your desired diagram in natural language ```bash python scripts/generate_schematic.py "your diagram description" -o figures/output.png ``` --- ## Automatic Backend Selection The skill automatically routes queries to the best backend based on content: ### Routing Logic ``` Query arrives | +-- Contains academic keywords? (papers, DOI, journal, peer-reviewed, etc.) | YES --> Perplexity sonar-pro-search (academic search mode) | +-- Needs deep multi-source synthesis? (user says "deep research", "exhaustive") | YES --> Parallel Chat API (core model, 60s-5min) | +-- Everything else (general research, market data, technical info, analysis) --> parallel-cli search (fast, default) ``` ### Default: parallel-cli search (parallel-web skill) **Primary backend for all standard research queries.** Fast, cost-effective, and supports academic source prioritization. For scientific/technical queries, run two searches to ensure academic coverage: ```bash # 1. Academic-focused search parallel-cli search "your research query" -q "keyword1" -q "keyword2" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ --include-domains "scholar.google.com,arxiv.org,pubmed.ncbi.nlm.nih.gov,semanticscholar.org,biorxiv.org,medrxiv.org,ncbi.nlm.nih.gov,nature.com,science.org,ieee.org,acm.org,springer.com,wiley.com,cell.com,pnas.org,nih.gov" \ -o sources/research_-academic.json # 2. General search (catches non-academic sources) parallel-cli search "your research query" -q "keyword1" -q "keyword2" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ -o sources/research_-general.json ``` Options: - `--after-date YYYY-MM-DD` for time-sensitive queries - `--include-domains domain1.com,domain2.com` to limit to specific sources Merge results, leading with academic sources. For non-scientific queries, a single general search is sufficient. All other queries route here by default, including: - General research questions - Market and industry analysis - Technical information and documentation - Current events and recent developments - Comparative analysis - Statistical data retrieval - Fact-checking and verification ### Academic Keywords (Routes to Perplexity) Queries containing these terms are routed to Perplexity for academic-focused search: - Paper finding: `find papers`, `find articles`, `research papers on`, `published studies` - Citations: `cite`, `citation`, `doi`, `pubmed`, `pmid` - Academic sources: `peer-reviewed`, `journal article`, `scholarly`, `arxiv`, `preprint` - Review types: `systematic review`, `meta-analysis`, `literature search` - Paper quality: `foundational papers`, `seminal papers`, `landmark papers`, `highly cited` ### Deep Research (Routes to Parallel Chat API) Only used when the user explicitly requests deep, exhaustive, or comprehensive research. Much slower and more expensive than parallel-cli search. ### Manual Override You can force a specific backend: ```bash # Force parallel-cli search (fast web search) parallel-cli search "your query" -q "keyword" --json --max-results 10 -o sources/research_.json # Force Parallel Deep Research (slow, exhaustive) python research_lookup.py "your query" --force-backend parallel # Force Perplexity academic search python research_lookup.py "your query" --force-backend perplexity ``` --- ## Core Capabilities ### 1. General Research Queries (parallel-cli search — DEFAULT) **Primary backend.** Fast, cost-effective web search with academic source prioritization via the parallel-web skill. ``` Query Examples: - "Recent advances in CRISPR gene editing 2025" - "Compare mRNA vaccines vs traditional vaccines for cancer treatment" - "AI adoption in healthcare industry statistics" - "Global renewable energy market trends and projections" - "Explain the mechanism underlying gut microbiome and depression" ``` ```bash # Example: research on CRISPR advances parallel-cli search "Recent advances in CRISPR gene editing 2025" \ -q "CRISPR" -q "gene editing" -q "2025" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ --include-domains "scholar.google.com,arxiv.org,pubmed.ncbi.nlm.nih.gov,nature.com,science.org,cell.com,pnas.org,nih.gov" \ -o sources/research_crispr_advances-academic.json parallel-cli search "Recent advances in CRISPR gene editing 2025" \ -q "CRISPR" -q "gene editing" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ -o sources/research_crispr_advances-general.json ``` **Response includes:** - Synthesized findings with inline citations from search results - Academic sources prioritized (peer-reviewed, preprints) - Specific facts, numbers, and dates - Sources section listing all referenced URLs grouped by type ### 2. Academic Paper Search (Perplexity sonar-pro-search) **Used for academic-specific queries.** Prioritizes scholarly databases and peer-reviewed sources. Use when queries specifically ask for papers, citations, or DOIs. ``` Query Examples: - "Find papers on transformer attention mechanisms in NeurIPS 2024" - "Foundational papers on quantum error correction" - "Systematic review of immunotherapy in non-small cell lung cancer" - "Cite the original BERT paper and its most influential follow-ups" - "Published studies on CRISPR off-target effects in clinical trials" ``` **Response includes:** - Summary of key findings from academic literature - 5-8 high-quality citations with authors, titles, journals, years, DOIs - Citation counts and venue tier indicators - Key statistics and methodology highlights - Research gaps and future directions ### 3. Deep Research (Parallel Chat API — on request only) **Used only when user explicitly requests deep/exhaustive research.** Provides comprehensive, multi-source synthesis via the Chat API (`core` model). 60s-5min latency. ``` Query Examples: - "Deep research on the current state of quantum computing error correction" - "Exhaustive analysis of mRNA vaccine platforms for cancer immunotherapy" ``` ### 4. Technical and Methodological Information Use parallel-cli search (default) for quick lookups: ```bash parallel-cli search "Western blot protocol for protein detection" \ -q "western blot" -q "protocol" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ -o sources/research_western_blot.json ``` ### 5. Statistical and Market Data Use parallel-cli search (default) for current data: ```bash parallel-cli search "Global AI market size and growth projections 2025" \ -q "AI market" -q "statistics" -q "growth" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ --after-date 2024-01-01 \ -o sources/research_ai_market.json ``` --- ## Paper Quality and Popularity Prioritization **CRITICAL**: When searching for papers, ALWAYS prioritize high-quality, influential papers. ### Citation-Based Ranking | Paper Age | Citation Threshold | Classification | |-----------|-------------------|----------------| | 0-3 years | 20+ citations | Noteworthy | | 0-3 years | 100+ citations | Highly Influential | | 3-7 years | 100+ citations | Significant | | 3-7 years | 500+ citations | Landmark Paper | | 7+ years | 500+ citations | Seminal Work | | 7+ years | 1000+ citations | Foundational | ### Venue Quality Tiers **Tier 1 - Premier Venues** (Always prefer): - **General Science**: Nature, Science, Cell, PNAS - **Medicine**: NEJM, Lancet, JAMA, BMJ - **Field-Specific**: Nature Medicine, Nature Biotechnology, Nature Methods - **Top CS/AI**: NeurIPS, ICML, ICLR, ACL, CVPR **Tier 2 - High-Impact Specialized** (Strong preference): - Journals with Impact Factor > 10 - Top conferences in subfields (EMNLP, NAACL, ECCV, MICCAI) **Tier 3 - Respected Specialized** (Include when relevant): - Journals with Impact Factor 5-10 --- ## Technical Integration ### Prerequisites ```bash # Primary backend (parallel-cli) - REQUIRED # Install parallel-cli if not already available: curl -fsSL https://parallel.ai/install.sh | bash # Or: uv tool install "parallel-web-tools[cli]" # Authenticate: parallel-cli auth # Or: export PARALLEL_API_KEY="your_parallel_api_key" ``` ### Environment Variables ```bash # Primary backend (parallel-cli search) - REQUIRED export PARALLEL_API_KEY="your_parallel_api_key" # Deep research backend (Parallel Chat API) - optional, for deep research only # Uses the same PARALLEL_API_KEY # Academic search backend (Perplexity) - optional, for academic paper queries export OPENROUTER_API_KEY="your_openrouter_api_key" ``` ### API Specifications **parallel-cli search (PRIMARY):** - Command: `parallel-cli search` with `--json` output - Latency: 2-10 seconds (fast) - Output: JSON with title, URL, publish_date, excerpts - Academic domains: Use `--include-domains` for scholarly sources - Saves results: `-o filename.json` for follow-up and reproducibility **Parallel Chat API (deep research only):** - Endpoint: `https://api.parallel.ai` (OpenAI SDK compatible) - Model: `core` (60s-5min latency, complex multi-source synthesis) - Output: Markdown text with inline citations - Citations: Research basis with URLs, reasoning, and confidence levels - Rate limits: 300 req/min - Python package: `openai` **Perplexity sonar-pro-search (academic only):** - Model: `perplexity/sonar-pro-search` (via OpenRouter) - Search mode: Academic (prioritizes peer-reviewed sources) - Search context: High (comprehensive research) - Response time: 5-15 seconds ### Command-Line Usage ```bash # Fast web search via parallel-cli (DEFAULT — recommended) — ALWAYS save to sources/ parallel-cli search "your query" -q "keyword1" -q "keyword2" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ -o sources/research_.json # Academic-focused search via parallel-cli — ALWAYS save to sources/ parallel-cli search "your query" -q "keyword1" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ --include-domains "scholar.google.com,arxiv.org,pubmed.ncbi.nlm.nih.gov,semanticscholar.org,biorxiv.org,medrxiv.org,nature.com,science.org,cell.com,pnas.org,nih.gov" \ -o sources/research_-academic.json # Time-sensitive search via parallel-cli parallel-cli search "your query" -q "keyword" \ --json --max-results 10 --after-date 2024-01-01 \ -o sources/research_.json # Extract full content from a specific URL (use parallel-web extract) parallel-cli extract "https://example.com/paper" --json # Force Parallel Deep Research (slow, exhaustive) — via research_lookup.py python research_lookup.py "your query" --force-backend parallel -o sources/research_.md # Force Perplexity academic search — via research_lookup.py python research_lookup.py "your query" --force-backend perplexity -o sources/papers_.md # Auto-routed via research_lookup.py (legacy) — ALWAYS save to sources/ python research_lookup.py "your query" -o sources/research_YYYYMMDD_HHMMSS_.md # Batch queries via research_lookup.py — ALWAYS save to sources/ python research_lookup.py --batch "query 1" "query 2" "query 3" -o sources/batch_research_.md ``` --- ## MANDATORY: Save All Results to Sources Folder **Every research-lookup result MUST be saved to the project's `sources/` folder.** This is non-negotiable. Research results are expensive to obtain and critical for reproducibility. ### Saving Rules | Backend | `-o` Flag Target | Filename Pattern | |---------|-----------------|------------------| | parallel-cli search (default) | `sources/research_.json` | `research_.json` or `research_-academic.json` | | Parallel Deep Research | `sources/research_.md` | `research_YYYYMMDD_HHMMSS_.md` | | Perplexity (academic) | `sources/papers_.md` | `papers_YYYYMMDD_HHMMSS_.md` | | Batch queries | `sources/batch_.md` | `batch_research_YYYYMMDD_HHMMSS_.md` | ### How to Save **CRITICAL: Every search MUST save results to the `sources/` folder using the `-o` flag.** **CRITICAL: Saved files MUST preserve all citations, source URLs, and DOIs.** ```bash # parallel-cli search (DEFAULT) — save JSON to sources/ parallel-cli search "Recent advances in CRISPR gene editing 2025" \ -q "CRISPR" -q "gene editing" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ --include-domains "scholar.google.com,arxiv.org,pubmed.ncbi.nlm.nih.gov,nature.com,science.org,cell.com,pnas.org,nih.gov" \ -o sources/research_crispr_advances-academic.json parallel-cli search "Recent advances in CRISPR gene editing 2025" \ -q "CRISPR" -q "gene editing" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ -o sources/research_crispr_advances-general.json # Academic paper search via Perplexity — save to sources/ python research_lookup.py "Find papers on transformer attention mechanisms in NeurIPS 2024" \ -o sources/papers_20250217_143500_transformer_attention.md # Deep research via Parallel Chat API — save to sources/ python research_lookup.py "AI regulation landscape" --force-backend parallel \ -o sources/research_20250217_144000_ai_regulation.md # Batch queries — save to sources/ python research_lookup.py --batch "mRNA vaccines efficacy" "mRNA vaccines safety" \ -o sources/batch_research_20250217_144500_mrna_vaccines.md ``` ### Citation Preservation in Saved Files Each output format preserves citations differently: | Format | Citations Included | When to Use | |--------|-------------------|-------------| | parallel-cli JSON (default) | Full result objects: `title`, `url`, `publish_date`, `excerpts` | Standard use — structured, parseable, fast | | Text (research_lookup.py) | `Sources (N):` section with `[title] (date) + URL` + `Additional References (N):` with DOIs and academic URLs | Deep research / Perplexity — human-readable | | JSON (`--json` via research_lookup.py) | Full citation objects: `url`, `title`, `date`, `snippet`, `doi`, `type` | When you need maximum citation metadata from deep research | **For parallel-cli search**, saved JSON files include: full search results with title, URL, publish date, and content excerpts for each result. **For Parallel Chat API backend**, saved files include: research report + Sources list (title, URL) + Additional References (DOIs, academic URLs). **For Perplexity backend**, saved files include: academic summary + Sources list (title, date, URL, snippet) + Additional References (DOIs, academic URLs). **Use `--json` when you need to:** - Parse citation metadata programmatically - Preserve full DOI and URL data for BibTeX generation - Maintain the structured citation objects for cross-referencing ### Why Save Everything 1. **Reproducibility**: Every citation and claim can be traced back to its raw research source 2. **Context Window Recovery**: If context is compacted, saved results can be re-read without re-querying 3. **Audit Trail**: The `sources/` folder documents exactly how all research information was gathered 4. **Reuse Across Sections**: Multiple sections can reference the same saved research without duplicate queries 5. **Cost Efficiency**: Check `sources/` for existing results before making new API calls 6. **Peer Review Support**: Reviewers can verify the research backing every citation ### Before Making a New Query, Check Sources First Before calling `research_lookup.py`, check if a relevant result already exists: ```bash ls sources/ # Check existing saved results ``` If a prior lookup covers the same topic, re-read the saved file instead of making a new API call. ### Logging When saving research results, always log: ``` [HH:MM:SS] SAVED: Research lookup to sources/research_20250217_143000_crispr_advances.md (3,800 words, 8 citations) [HH:MM:SS] SAVED: Paper search to sources/papers_20250217_143500_transformer_attention.md (6 papers found) ``` --- ## Integration with Scientific Writing This skill enhances scientific writing by providing: 1. **Literature Review Support**: Gather current research for introduction and discussion — **save to `sources/`** 2. **Methods Validation**: Verify protocols against current standards — **save to `sources/`** 3. **Results Contextualization**: Compare findings with recent similar studies — **save to `sources/`** 4. **Discussion Enhancement**: Support arguments with latest evidence — **save to `sources/`** 5. **Citation Management**: Provide properly formatted citations — **save to `sources/`** ## Complementary Tools | Task | Tool | |------|------| | General web search (fast) | `parallel-cli search` (built into this skill) | | Academic-focused web search | `parallel-cli search --include-domains` (built into this skill) | | URL content extraction | `parallel-cli extract` (parallel-web skill) | | Deep research (exhaustive) | `research-lookup` via Parallel Chat API or `parallel-web` deep research | | Academic paper search | `research-lookup` (auto-routes to Perplexity) | | Google Scholar search | `citation-management` skill | | PubMed search | `citation-management` skill | | DOI to BibTeX | `citation-management` skill | | Metadata verification | `parallel-cli extract` (parallel-web skill) | --- ## Error Handling and Limitations **Known Limitations:** - parallel-cli search: Requires `parallel-cli` to be installed and authenticated - Parallel Chat API (core model): Complex queries may take up to 5 minutes - Perplexity: Information cutoff, may not access full text behind paywalls - All backends: Cannot access proprietary or restricted databases **Fallback Behavior:** - If `parallel-cli` is not found, install with `curl -fsSL https://parallel.ai/install.sh | bash` or `uv tool install "parallel-web-tools[cli]"` - If parallel-cli search returns insufficient results, fall back to Perplexity or Parallel Chat API - If the selected backend's API key is missing, tries the other backend - If all backends fail, returns structured error response - Rephrase queries for better results if initial response is insufficient --- ## Usage Examples ### Example 1: General Research (Routes to parallel-cli search) **Query**: "Recent advances in transformer attention mechanisms 2025" **Backend**: parallel-cli search (default, fast) **Commands**: ```bash parallel-cli search "Recent advances in transformer attention mechanisms 2025" \ -q "transformer" -q "attention" -q "2025" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ --include-domains "arxiv.org,semanticscholar.org,nature.com,science.org,ieee.org,acm.org" \ -o sources/research_transformer_attention-academic.json parallel-cli search "Recent advances in transformer attention mechanisms 2025" \ -q "transformer" -q "attention" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ -o sources/research_transformer_attention-general.json ``` **Response**: Synthesized findings with inline citations from academic and general sources, covering recent papers, key innovations, and performance benchmarks. ### Example 2: Academic Paper Search (Routes to Perplexity) **Query**: "Find papers on CRISPR off-target effects in clinical trials" **Backend**: Perplexity sonar-pro-search (academic mode) **Response**: Curated list of 5-8 high-impact papers with full citations, DOIs, citation counts, and venue tier indicators. ### Example 3: Comparative Analysis (Routes to parallel-cli search) **Query**: "Compare and contrast mRNA vaccines vs traditional vaccines for cancer treatment" **Backend**: parallel-cli search (default, fast) **Response**: Synthesized comparison from multiple web sources with inline citations, structured analysis, and evidence quality notes. ### Example 4: Market Data (Routes to parallel-cli search) **Query**: "Global AI adoption in healthcare statistics 2025" **Backend**: parallel-cli search (default, fast) ```bash parallel-cli search "Global AI adoption in healthcare statistics 2025" \ -q "AI healthcare" -q "adoption statistics" \ --json --max-results 10 --excerpt-max-chars-total 27000 \ --after-date 2024-01-01 \ -o sources/research_ai_healthcare_adoption.json ``` **Response**: Current market data, adoption rates, growth projections, and regional analysis with source citations. --- ## Summary This skill serves as the primary research interface with intelligent tri-backend routing: - **parallel-cli search** (default): Fast, cost-effective web search with academic source prioritization via the parallel-web skill - **Parallel Chat API** (`core` model): Deep, exhaustive multi-source synthesis (on explicit request only) - **Perplexity sonar-pro-search**: Academic-specific paper searches only - **Automatic routing**: Detects query type and routes to the optimal backend - **Manual override**: Force any backend when needed - **Academic prioritization**: Two-search pattern ensures scholarly sources surface for scientific queries