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. Note: query text is transmitted to api.parallel.ai (PARALLEL_API_KEY) and, for academic searches, to openrouter.ai (OPENROUTER_API_KEY).
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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. Note: query text is transmitted to api.parallel.ai (PARALLEL_API_KEY) and, for academic searches, to openrouter.ai (OPENROUTER_API_KEY).
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
required_environment_variables
[{"name":"PARALLEL_API_KEY","prompt":"Parallel web search API key.","required_for":"optional features"},{"name":"OPENROUTER_API_KEY","prompt":"OpenRouter API key (fallback model access).","required_for":"optional features"}]
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
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"
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:
# Primary backend (parallel-cli search) - REQUIREDexport 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 queriesexport 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
# 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
Backend
-o Flag Target
Filename Pattern
parallel-cli search (default)
sources/research_<topic>.json
research_<brief_topic>.json or research_<brief_topic>-academic.json
Parallel Deep Research
sources/research_<topic>.md
research_YYYYMMDD_HHMMSS_<brief_topic>.md
Perplexity (academic)
sources/papers_<topic>.md
papers_YYYYMMDD_HHMMSS_<brief_topic>.md
Batch queries
sources/batch_<topic>.md
batch_research_YYYYMMDD_HHMMSS_<brief_topic>.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.
# 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
Reproducibility: Every citation and claim can be traced back to its raw research source
Context Window Recovery: If context is compacted, saved results can be re-read without re-querying
Audit Trail: The sources/ folder documents exactly how all research information was gathered
Reuse Across Sections: Multiple sections can reference the same saved research without duplicate queries
Cost Efficiency: Check sources/ for existing results before making new API calls
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:
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:
Literature Review Support: Gather current research for introduction and discussion — save to sources/
Methods Validation: Verify protocols against current standards — save to sources/
Results Contextualization: Compare findings with recent similar studies — save to sources/
Discussion Enhancement: Support arguments with latest evidence — save to sources/
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"
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"
