10-of-my-most-popular-text-to-image-series-prompts-78b0897e
generate a bunch of images, then you curate the results to handpick the best ones
Search research papers and get publication details from Clarity Protocol. Use when the user asks to search research papers, find publications, PubMed references, literature about protein, or citation details. Capabilities: search papers, get paper details by PMID.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install clarityprotocol/clarity-literature打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Search and retrieve research papers from Clarity Protocol's curated literature database, sourced from PubMed and enriched with citation metrics from Semantic Scholar.
List all papers in the database:
python scripts/search_papers.py
Get details for a specific paper by PMID:
python scripts/get_paper.py --pmid 12345678
Get paper details in readable format:
python scripts/get_paper.py --pmid 12345678 --format summary
Each paper includes:
pmid: PubMed identifierdoi: Digital Object Identifiertitle: Paper titlefirst_author: First author namepublication_year: Year publishedjournal: Journal nameabstract: Paper abstract (when available)citation_count: Number of citations (from Semantic Scholar)influential_citations: Number of highly influential citationshas_fulltext: Whether full text is available in PubMed CentralTo use an API key, set the CLARITY_API_KEY environment variable:
export CLARITY_API_KEY=your_key_here
python scripts/search_papers.py
Get your API key at https://clarityprotocol.io
404 Not Found: The paper with the specified PMID does not exist in the database.
429 Rate Limit: You've exceeded the rate limit. The script will display how long to wait.
500 Server Error: The API server encountered an error. Try again later.
Timeout: The request took longer than 30 seconds.
Paper lists are paginated. The API returns a next_cursor field if more results are available.
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# Clarity Literature Skill Search and retrieve research papers from Clarity Protocol's curated literature database, sourced from PubMed and enriched with citation metrics from Semantic Scholar. ## Quick Start List all papers in the database: ```bash python scripts/search_papers.py ``` Get details for a specific paper by PMID: ```bash python scripts/get_paper.py --pmid 12345678 ``` Get paper details in readable format: ```bash python scripts/get_paper.py --pmid 12345678 --format summary ``` ## Paper Fields Each paper includes: - `pmid`: PubMed identifier - `doi`: Digital Object Identifier - `title`: Paper title - `first_author`: First author name - `publication_year`: Year published - `journal`: Journal name - `abstract`: Paper abstract (when available) - `citation_count`: Number of citations (from Semantic Scholar) - `influential_citations`: Number of highly influential citations - `has_fulltext`: Whether full text is available in PubMed Central ## Rate Limits - **Anonymous (no API key)**: 10 requests/minute - **With API key**: 100 requests/minute To use an API key, set the `CLARITY_API_KEY` environment variable: ```bash export CLARITY_API_KEY=your_key_here python scripts/search_papers.py ``` Get your API key at https://clarityprotocol.io ## Error Handling **404 Not Found**: The paper with the specified PMID does not exist in the database. **429 Rate Limit**: You've exceeded the rate limit. The script will display how long to wait. **500 Server Error**: The API server encountered an error. Try again later. **Timeout**: The request took longer than 30 seconds. ## Pagination Paper lists are paginated. The API returns a `next_cursor` field if more results are available. ## Use Cases - Find research papers related to protein variants - Get citation metrics for a specific paper - Check if a paper has full text available - Extract abstracts for literature reviews - Build bibliographies for protein research
generate a bunch of images, then you curate the results to handpick the best ones
generate a bunch of images, then you curate the results to handpick the best ones
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