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  1. Home
  2. Development
  3. Lead Research Assistant
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Lead Research Assistant

Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.

ComposioHQ

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

#git#markdown

Technical Information

Author
ComposioHQ
Category
Development
File Size
6.43 KB
Source Repository
ComposioHQ__awesome-claude-skills
Metadata
Includes YAML metadata
License
MIT

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

ComposioHQ__awesome-claude-skills/lead-research-assistant/skill.md

Why Choose This Skill

Proven benefits and measurable impact

10x

Faster Structure Retrieval

Access 200M+ protein structures instantly compared to manual search.

50%

Reduced Experimental Costs

Cut wet lab expenses by using AI predictions for initial screening.

3x

Higher Research Throughput

Analyze multiple protein structures in parallel with automated tools.

Use Cases

Perfect for these scenarios

🔬

Drug Discovery

Identify binding sites in novel protein structures for drug targeting.

🧬

Protein Engineering

Modify protein sequences to enhance stability or functionality.

📊

Structural Analysis

Evaluate confidence metrics for accurate protein folding predictions.

🧪

Research Validation

Cross-reference predicted structures with experimental data for validation.

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