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Claude Code Expert

Expert on Claude Code CLI, skills, commands, hooks, plugins, MCP, settings, and workflows. Triggers on claude code, cli, skill, command, hook, plugin, mcp, slash command, settings

raintree-technology

Core Features

Ready to Use

Quick integration into your workflow with minimal setup

Community Verified

Active open-source community with continuous updates

Completely Free

MIT/Apache licensed for commercial and personal use

Flexible Extension

Customizable and extendable based on your needs

How to Use

1Get Skill File

Download or copy the skill file from the source repository

2Install to Claude

Place the skill file in Claude's skills directory (usually ~/.claude/skills/)。

3Start Using

Restart Claude or run the reload command to load the skill

Tip: Read the documentation and code carefully before first use to understand functionality and permission requirements

Related Tags

#automation#ci-cd#debugging#docker#documentation#markdown#security#testing

Technical Information

Author
raintree-technology
Category
Development
File Size
4.82 KB
Source Repository
raintree-technology__claude-starter
Metadata
Includes YAML metadata
License
MIT

All Skills from open-source community, preserving original authors' copyrights

raintree-technology__claude-starter/.claude/skills/anthropic/claude-code/Skill.md

Why Choose This Skill

Proven benefits and measurable impact

80%

Time Savings

Reduce data exploration time with automated format detection and analysis reporting

5x

Error Reduction

Catch format issues and quality problems early in the analysis workflow

200+

Format Coverage

Support more scientific data formats than any manual or specialized tool

Use Cases

Perfect for these scenarios

🧪

Chemistry Data QC

Validate and summarize NMR, mass spec, or chromatography data formats for research integrity

🧬

Bioinformatics Pipeline Prep

Analyze FASTQ, BAM, or VCF files before genome analysis workflows or machine learning

🔬

Microscopy Data Insights

Explore image stacks and metadata from confocal or electron microscopy experiments

📊

Multi-Omics Integration

Characterize proteomics, metabolomics, or transcriptomics datasets before cross-platform analysis

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