research-lookup
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).
npx skills add majiayu000/claude-skill-registry --skill research-lookup-k-dense-ai-scientific-agent-ski-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Looks up current research information by automatically routing queries to the best backend among parallel-cli search (primary, fast web search), Parallel Chat API (deep research), and Perplexity sonar-pro-search (academic paper searches). It is meant 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).
How it works
- Uses parallel-cli search as the default backend for general research queries, with academic sources prioritized via --include-domains.
- Routes to Perplexity sonar-pro-search when academic-specific searches are requested (academic keywords detected) and to Parallel Chat API for deep, multi-source synthesis when explicitly needed.
- Provides two searches for scientific/technical queries to ensure academic coverage: one academic-focused and one general search, then merges results with academic sources leading.
- Outputs are saved to sources/ with a specific filename pattern, and include citations, URLs, and DOIs.
When to use it
Use when you need current research information, literature verification, background research, citation sources, technical documentation, market/industry data, or recent developments.
What it can touch
- Command examples show usage of: parallel-cli, parallel web domains, and save outputs to sources/ (JSON and MD formats). Tools allowed: Read, Write, Edit, Bash.
- Saving rules require outputs to be saved in sources/ using -o flags for various backends.
Caveats
- Query text may be transmitted to PARALLEL_API_KEY backend and OPENROUTER_API_KEY for academic queries. License is MIT. Requires parallel-cli as primary backend; OPENROUTER_API_KEY is optional for academic searches.
# 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
- Overview
- When to Use This Skill
- Visual Enhancement with Scientific Schematics
- Automatic Backend Selection
- Routing Logic
- Default: parallel-cli search (parallel-web skill)
- Academic Keywords (Routes to Perplexity)
- Deep Research (Routes to Parallel Chat API)
- Manual Override
- Core Capabilities
- 1. General Research Queries (parallel-cli search — DEFAULT)
- 2. Academic Paper Search (Perplexity sonar-pro-search)
- 3. Deep Research (Parallel Chat API — on request only)
- 4. Technical and Methodological Information
python scripts/generate_schematic.py "your diagram description" -o figures/output.png parallel-cli search "your research query" -q "keyword1" -q "keyword2" \ 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 parallel-cli search "Recent advances in CRISPR gene editing 2025" \ parallel-cli search "Western blot protocol for protein detection" \
What does the research-lookup skill do?
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).
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill research-lookup-k-dense-ai-scientific-agent-ski-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.