meishiwhy/literature-mind/litmind-review

Claude Code and agent skill by meishiwhy/literature-mind

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LitMind Review Generator — 基于科研知识库的综述生成系统

Install

npx vskill@latest install meishiwhy/literature-mind/litmind-review

SKILL.md

LitMind Review Generator

输入研究主题，自动检索知识库相关文献，分析研究趋势、主题聚类、共识与争议，生成结构化综述框架和带引用的综述草稿。

工作流程

  1. 检索 KB 获取相关论文
  2. ThemeDiscoveryEngine 聚类主题
  3. TrendAnalyzer 统计高频变量/方法/设计
  4. ConsensusAnalyzer 识别研究共识
  5. ControversyAnalyzer 识别研究争议
  6. GapAnalyzer 发现研究空白
  7. OutlineGenerator 生成综述框架
  8. ReviewComposer 生成综述全文

输出结构

  • researchThemes — 研究主题聚类
  • researchConsensus — 研究共识
  • researchControversies — 研究争议
  • researchGaps — 研究空白
  • reviewOutline — 综述框架
  • reviewDraft — 综述全文

调用方式

Python API
python
from litmind_knowledge.service import KnowledgeBase
from litmind_evidence import EvidenceFinderService
from litmind_review import ReviewGeneratorService, ReviewInput
from litmind_analyzer.providers import AnthropicProvider
kb = KnowledgeBase()
provider = AnthropicProvider()
ev = EvidenceFinderService(kb=kb, llm_provider=provider)
service = ReviewGeneratorService(kb=kb, evidence_service=ev, llm_provider=provider)
result = service.generate_review(ReviewInput(topic="Flatfoot Biomechanics"))
print("Themes:", len(result.researchThemes))
print("Draft:", len(result.reviewDraft), "chars")
python
from litmind_knowledge.service import KnowledgeBase
from litmind_evidence import EvidenceFinderService
from litmind_review import ReviewGeneratorService, ReviewInput
from litmind_analyzer.providers import AnthropicProvider
kb = KnowledgeBase()
provider = AnthropicProvider()
ev = EvidenceFinderService(kb=kb, llm_provider=provider)
service = ReviewGeneratorService(kb=kb, evidence_service=ev, llm_provider=provider)
result = service.generate_review(ReviewInput(topic="Flatfoot Biomechanics"))
print(f"Themes: {len(result.researchThemes)}")
print(f"Draft: {len(result.reviewDraft)} chars")

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Source

Popularity

Repository stars
102
Repository forks
2
7-day trend score
23

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