Agent skill · AI & Agents

kegg-analysis

Multi-step KEGG bioinformatics workflows — pathway enrichment from gene lists, drug-target investigation, cross-species metabolic comparison, and compound-reaction network exploration. Guides Claude through the full analytical pipeline using KEGG MCP tools.

Dave Poon3,251★ · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add davepoon/buildwithclaude --skill kegg-analysis --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 4 KB
Bundled scripts: none
Path: plugins/kegg-mcp-server/skills/kegg-analysis/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,251
Language: TypeScript
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# KEGG Bioinformatics Analysis This skill orchestrates multi-step biological analyses using the KEGG MCP server tools. It transforms raw gene lists, drug names, or pathway IDs into structured biological insights. ## When to Use This Skill - Performing pathway enrichment analysis on a gene list - Investigating a drug's mechanism of action, targets, and interactions - Comparing metabolic pathways ac

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About this skill
What does the kegg-analysis skill do?

Multi-step KEGG bioinformatics workflows — pathway enrichment from gene lists, drug-target investigation, cross-species metabolic comparison, and compound-reaction network exploration. Guides Claude through the full analytical pipeline using KEGG MCP tools.

How do I install it?

Run `npx skills add davepoon/buildwithclaude --skill kegg-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From davepoon/buildwithclaude, a repository with 3,251 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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