meishiwhy/literature-mind/litmind-discussion

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LitMind Discussion Generator — 基于证据的 Discussion 草稿生成

Install

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

SKILL.md

LitMind Discussion Generator

输入研究主题和结果，自动检索 Knowledge Base 中的文献证据，生成具有科学依据和可追溯引用的 Discussion 草稿。

工作流程

  1. 解析用户输入的研究结果
  2. Evidence Finder 检索支持/反对证据
  3. DiscussionComposer 逐步生成 7 个 Section
  4. CitationManager 确保所有论述可追溯

输出结构

Section内容
Main Finding Interpretation主要发现解读
Supporting Evidence支持证据对比
Contradictory Evidence矛盾证据讨论
Potential Mechanisms潜在机制解释
Practical Implications实践意义
Study Limitations研究局限性
Future Directions未来方向

调用方式

Python API
python
from litmind_knowledge.service import KnowledgeBase
from litmind_evidence import EvidenceFinderService
from litmind_discussion import DiscussionGeneratorService, DiscussionInput
from litmind_analyzer.providers import AnthropicProvider
kb = KnowledgeBase()
provider = AnthropicProvider()
ev_service = EvidenceFinderService(kb=kb, llm_provider=provider)
service = DiscussionGeneratorService(evidence_service=ev_service, llm_provider=provider)
inp = DiscussionInput(studyTopic="Footwear stiffness", results=["High stiffness increased MTP ROM"])
result = service.generate_discussion(inp)
print(result.discussionDraft)
print("Citations:", len(result.citations))
python
from litmind_knowledge.service import KnowledgeBase
from litmind_evidence import EvidenceFinderService
from litmind_discussion import DiscussionGeneratorService, DiscussionInput
from litmind_analyzer.providers import AnthropicProvider
kb = KnowledgeBase()
provider = AnthropicProvider()
ev_service = EvidenceFinderService(kb=kb, llm_provider=provider)
service = DiscussionGeneratorService(evidence_service=ev_service, llm_provider=provider)
inp = DiscussionInput(studyTopic="Footwear stiffness", results=["High stiffness increased MTP ROM"])
result = service.generate_discussion(inp)
print(result.discussionDraft)
print(f"Citations: {len(result.citations)}")

引用安全

所有引用均来自 Knowledge Base，LLM 只能引用白名单内的 paperId。

Security

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  • Model reviewPassed

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Source

Popularity

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

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