---
name: literature
description: # Literature Search & Review
---

# Literature Search & Review

## Overview
Comprehensive academic literature search and synthesis across 15+ sources.

## Capabilities
- Multi-database parallel search (PubMed, arXiv, bioRxiv, medRxiv, OpenAlex, Semantic Scholar, Crossref, DBLP, CORE, DOAJ, Europe PMC)
- Web search via Agent-Reach (Exa semantic search, Jina Reader for any URL/PDF)
- Social academic search (Twitter/X threads, YouTube talks, GitHub repos)
- Structured literature reviews with citation networks
- Knowledge gap identification
- Hypothesis generation from literature analysis

## Search Strategy
1. **Query optimization**: Short, keyword-based queries (max 7 words). PubMed-friendly syntax.
2. **Multi-source fan-out**: Parallel queries across all sources for maximum coverage.
3. **Deduplication**: By PMID, DOI, then normalized title.
4. **Reflection loop**: Evaluate coverage → identify gaps → generate follow-up queries.

## Citation Rules
- ZERO hallucinated citations. Every reference must come from real search data.
- Unified article schema: source_type, title, authors, year, journal, url, doi, pmid, abstract.
- Numbered references [1], [2], [3] — built only from retrieved articles.

## Best Practices
- Start broad, then narrow. First search finds the landscape; follow-up queries fill gaps.
- Cross-domain search. The breakthrough paper might be in an unexpected field.
- Check preprints AND published papers. Recent findings may only be on bioRxiv/arXiv.
- Verify high-impact claims. Use Semantic Scholar's citation count to identify landmark papers.


---
Source attribution: beita6969
Original project: https://github.com/beita6969/ScienceClaw/blob/e925f732c7ca435f557e88075bc47a58f1e984f1/skills/literature/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2025 Peter Steinberger

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: beita6969
Original project: https://github.com/beita6969/ScienceClaw/blob/e925f732c7ca435f557e88075bc47a58f1e984f1/skills/literature/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Education & Research
Roles: Academic Writer, Data Analyst, Researcher
Specialties: Specialty not specified
Tools: Arxiv, Core, Crossref, Doaj, Europe Pmc, Github, Pubmed, Semantic Scholar, Twitter, Youtube
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 1a8b68a95cc83acaaf86d75beb6ba8c9ab137efe64c78153815d2228f800b12e