Individual skill
scispark
从天文关键词、论文或已有结果提出可检验的研究假设,分别记录事实、推测和检验方法,并保留论文编号与核验状态。
skills/scispark/SKILL.md
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- No
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- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 11, 2026
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Repository context
- Repository stars (not skill ratings)
- 331
- Repository last updated
- Oct 19, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- astronomy Repository topic
- astrophysics Repository topic
- large-language-models Repository topic
- llm Repository topic
- agents Repository topic
- ai4s Repository topic
- telescope Repository topic
- time-domain-astronomy Repository topic
- engineering Derived category
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SKILL.mdcore · 2,332 bytesSKILL.mdcore · 2,332 bytesagents/openai.yamlasset · 293 bytesassets/final_idea_template.mddoc · 1,587 bytesastronomy.mddoc · 1,798 bytesreferences/arxiv-integration.mddoc · 2,058 bytesreferences/scispark-workflow.mddoc · 6,530 bytesreferences/stage-contracts.mddoc · 2,617 bytesscripts/init_scispark_workspace.pyruns · 2,629 bytesscripts/search_arxiv.pyruns · 3,161 bytes
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# 研究假设与检验方法
从关键词、论文或已有结果提出可检验的天文假设。事实、推测、方法与最终方案分别记录,每个关键论述应有文献依据或明确的限制。
## 怎么开始
明确关键词、研究范围、已有论文与本次要做到哪一步。天文证据要求见 [astronomy.md](astronomy.md)。初始化脚本在本技能目录运行:
```bash
python scripts/init_scispark_workspace.py "稀疏光变早期分类"
```
默认工作目录为 `./scispark/<课题名>/`。脚本 `search_arxiv.py` 查询 arXiv;ADS 检索或已有候选可由文献检索技能提供。正常推理使用当前模型,不需要另申请模型 API 密钥。