k-dense-ai/scientific-agent-skills

Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 175,000+ scientists worldwide. 163 ready-to-use validated skills...

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Summary Information

Updated 26 minutes ago
Added to GitGenius on August 26th, 2026
Created on October 19th, 2025
Open Issues & Pull Requests: 18 (+0)
GitHub issues: Enabled
Number of forks: 3,526
Total Stargazers: 37,153 (+66)
Total Subscribers: 168 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 46.5 hours
Mean response time: 11.3 days
90th percentile: 37.8 days
Tracked items: 77

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 24% of issues opened in the past year have been closed. Three people close 91% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 4
New in 7 days: 1
Closed in 7 days: 0
Avg open age: 55 days
Stale 30+ days: 2
Stale 90+ days: 0

Recent activity

Opened in 7 days: 1
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (2)
  • needs-triage (1)
  • skill-request (1)

Most active issues this week

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Detailed Description

Scientific Agent Skills is an agent skills library that extends any AI agent supporting the open Agent Skills standard with scientific and research capabilities.

The tool solves the problem of equipping AI agents with domain-specific knowledge and workflows for scientific research. It provides a collection of ready-to-use skills covering cancer genomics, pathogen surveillance, pharmacokinetic and pharmacodynamic modelling, biomedical literature retrieval, drug-target binding prediction, molecular dynamics, microbiome analysis, and geospatial science. The skills integrate with over 100 scientific databases spanning biology, chemistry, medicine, and drug discovery. Rather than requiring agents to learn these domains from scratch, the tool packages validated scientific workflows as discrete, callable skills that agents can invoke as part of their reasoning process.

Researchers, computational biologists, chemists, and drug discovery teams should adopt this tool if they use AI agents for scientific work and want to accelerate multi-step research workflows. It suits projects requiring integration with specialized scientific databases, literature retrieval, or complex analytical methods. The tool works with multiple agent platforms including Cursor, Claude Code, and any system supporting the Agent Skills standard, making it compatible across different AI environments. A complementary desktop application called K-Dense BYOK provides a standalone research workspace powered by these skills, allowing users to run workflows locally with their own API keys while optionally scaling to cloud compute.

The project maintains an active collection of scientific skills with regular expansion across new research domains. Development includes ongoing integration with scientific databases and computational methods, reflecting responsiveness to research community needs. The maintainers actively document workflows and provide educational resources including webinars and demonstrations for users adopting the skills in their research practice.