academic-scientific-research

Find, screen, and synthesize academic papers, scientific literature, technical reports, preprints, clinical or biomedical publications, and evidence around a…

npx skills add https://github.com/tavily-ai/use-case-skills --skill academic-scientific-research

Academic Scientific Research

Workflow

Use search to discover scholarly sources, extract to verify source content, map or crawl for known scholarly sites and collections, and research for full literature-review synthesis. Keep this skill focused on research planning, source selection, extraction targets, and evidence synthesis; execution mechanics should come from companion endpoint skills.

Treat the guidance below as base guidance; adapt it to the user's request when appropriate.

  • Translate the user's question into search terms, synonyms, key entities, and likely source domains.
  • Break broad questions into short subqueries under 400 characters: core concept, synonyms, method names, target population or data, benchmark or dataset, author/lab, and year range.
  • Prefer scholarly and official sources when available: preprint servers, PubMed/NIH pages, journals, conference proceedings, professional societies, standards bodies, and official technical reports.
  • Extract from the strongest selected pages after screening titles, snippets, source type, recency, and relevance.
  • Reserve broad research synthesis for full literature reviews, research landscapes, or multi-method comparisons.
  • Distinguish primary studies, review papers, preprints, editorials, guidelines, standards, and news coverage.

Research Budget

  • Start with a small focused search set covering the main concept, synonyms, methods, and source type.
  • Extract only the strongest scholarly sources before drafting the evidence brief.
  • Add more searches only for named gaps, such as missing review papers, missing recent work, or missing primary studies.
  • Do not use map unless a known lab, journal, conference, repository, or documentation site has buried pages.
  • Do not use crawl unless the user needs broad collection from a known proceedings, publication list, or docs section.

Capability Guidance

  • Use search first when the user needs papers, methods, benchmarks, authors, institutions, or recent work.
  • Use extract when comparing a small set of papers, reading abstracts, or verifying study claims.
  • Use map only when a known lab, journal, conference, repository, or documentation site has useful but hard-to-find pages.
  • Use crawl only when the user needs many pages from a known source, such as proceedings, a lab publication list, or a technical docs section.
  • Use research only when the user explicitly needs a full literature review or research landscape.

Query And Source Guidance

  • Pair formal terms with common synonyms and acronyms.
  • Include population, dataset, benchmark, organism, intervention, model, metric, or method terms when relevant.
  • For recent literature, include explicit year ranges or recency language in the query.
  • Prefer primary literature for claims, review papers for landscape summaries, and guidelines/standards for practice recommendations.
  • Deduplicate preprints and final publications; cite the final version when available.
  • Treat abstracts, papers, supplemental pages, tables, and official repositories as separate evidence surfaces.
  • Report failed or inaccessible sources when they affect key papers, guidelines, datasets, or primary evidence.

Output Template

Use this markdown structure and adapt sections to the user's scope:

# Evidence Brief: <topic>

## Research Question
<brief framing of the question>

## Search Strategy
- Concepts searched:
- Source types prioritized:
- Inclusion logic:
- Exclusions or limitations:

## Key Sources
| Source | Type | Why it matters | URL |
| --- | --- | --- | --- |

## Findings
### <Theme>
- Claim:
- Evidence:
- Limitations:

### <Theme>
- Claim:
- Evidence:
- Limitations:

## Consensus And Disagreement
- Consensus:
- Disagreement:
- Evidence gaps:

## Follow-Up Queries
- <query idea>

For medical, clinical, or biomedical topics, be conservative: do not provide diagnosis or treatment advice, and prioritize primary literature, systematic reviews, guidelines, and official health sources.

More skills from tavily-ai

research
tavily-ai
Comprehensive research on any topic with automatic source gathering, analysis, and citations. Conducts multi-source web research with explicit citations, ideal for comparisons, current events, market analysis, and detailed reports Offers three model options: mini for targeted single-topic research (~30s), pro for comprehensive multi-angle analysis (~60-120s), and auto for API-driven complexity detection Authenticates via OAuth through Tavily MCP server with automatic browser-based login on...
official
search
tavily-ai
Web search with LLM-optimized results, relevance scoring, and flexible filtering. Supports four search depth modes (ultra-fast, fast, basic, advanced) with configurable latency and relevance tradeoffs Includes domain filtering, time range constraints, date ranges, country boosting, and raw content extraction Returns results with title, URL, content snippet, and relevance score; optional image results and favicons Automatic OAuth authentication via Tavily MCP server or API key configuration;...
official
tavily-best-practices
tavily-ai
Web search API for LLMs with real-time data access, content extraction, site crawling, and AI-powered research. Five core methods: search() for web results, extract() for URL content, crawl() for site-wide extraction, map() for URL discovery, and research() for end-to-end AI synthesis Supports Python and JavaScript SDKs with async clients for parallel queries and configurable search depth (ultra-fast/fast/basic/advanced) Crawl method accepts semantic instructions to focus extraction on...
official
tavily-cli
tavily-ai
Web search, content extraction, site crawling, and deep research via Tavily CLI. Five command modes covering search, extraction, URL discovery, bulk crawling, and multi-source research with citations All commands support JSON output and file saving for structured, agentic workflows Escalation pattern guides you from simple search through extraction, mapping, crawling, to comprehensive research based on your needs Requires tavily-cli installation and API key authentication via tvly login
official
tavily-crawl
tavily-ai
Multi-page website crawler with semantic filtering and markdown export. Crawl entire site sections with depth and breadth control; filter by path regex, domain, or natural language instructions to focus results Save each page as local markdown files via --output-dir , or return structured JSON for agentic processing Use semantic instructions with chunk extraction to prevent context bloat when feeding results to LLMs; use full-page extraction for offline documentation downloads Supports...
official
tavily-dynamic-search
tavily-ai
Search the web, filter results, and extract content so that raw search data never enters your context window . Only your curated print() output comes back.
official
tavily-extract
tavily-ai
Extract clean markdown or text from up to 20 URLs, with JavaScript rendering and query-focused chunking support. Handles JavaScript-rendered pages with configurable extraction depth (basic for simple pages, advanced for dynamic SPAs and tables) Supports query-focused extraction to return only relevant content chunks instead of full pages Returns LLM-optimized markdown by default, with options for plain text format and structured JSON output Processes up to 20 URLs in a single call;...
official
tavily-map
tavily-ai
Fast URL discovery on websites without extracting content, ideal for finding specific pages on large sites. Returns structured lists of all URLs on a domain with configurable depth and breadth, regex path filtering, and natural language instructions for semantic filtering Supports depth control (1–5 levels), breadth limits per page, external link inclusion/exclusion, and domain filtering via regex patterns Designed as step 1 in a workflow: map to find the right page, then use extract or...
official