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

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:

# 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_<topic>-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_<topic>-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:

# Force parallel-cli search (fast web search)
parallel-cli search "your query" -q "keyword" --json --max-results 10 -o sources/research_<topic>.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"

# 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:

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:

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

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

# 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

# Primary backend (parallel-cli search) - REQUIRED

# 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

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

# 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_<topic>.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_<topic>-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_<topic>.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_<topic>.md

# Force Perplexity academic search — via research_lookup.py
python research_lookup.py "your query" --force-backend perplexity -o sources/papers_<topic>.md

# Auto-routed via research_lookup.py (legacy) — ALWAYS save to sources/
python research_lookup.py "your query" -o sources/research_YYYYMMDD_HHMMSS_<topic>.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_<topic>.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

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.

# 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 \\
  -