mirror of
https://github.com/K-Dense-AI/claude-scientific-skills.git
synced 2026-01-26 16:58:56 +08:00
3439a21f57
- Updated SKILL.md in citation management to include best practices for identifying seminal and high-impact papers, emphasizing citation count thresholds, venue quality tiers, and author reputation indicators. - Expanded literature review SKILL.md to prioritize high-impact papers, detailing citation metrics, journal tiers, and author reputation assessment. - Added comprehensive evaluation strategies for paper impact and quality in literature_search_strategies.md, including citation count significance and journal impact factor guidance. - Improved research lookup scripts to prioritize results based on citation count, venue prestige, and author reputation, enhancing the quality of research outputs.
90 lines
3.0 KiB
Bash
Executable File
90 lines
3.0 KiB
Bash
Executable File
#!/bin/bash
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# Example usage of AI-powered scientific schematic generation
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#
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# Prerequisites:
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# 1. Set OPENROUTER_API_KEY environment variable
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# 2. Ensure Python 3.10+ is installed
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# 3. Install requests: pip install requests
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set -e
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echo "=========================================="
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echo "Scientific Schematics - AI Generation"
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echo "Example Usage Demonstrations"
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echo "=========================================="
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echo ""
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# Check for API key
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if [ -z "$OPENROUTER_API_KEY" ]; then
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echo "❌ Error: OPENROUTER_API_KEY environment variable not set"
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echo ""
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echo "Get an API key at: https://openrouter.ai/keys"
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echo "Then set it with: export OPENROUTER_API_KEY='your_key'"
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exit 1
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fi
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echo "✓ OPENROUTER_API_KEY is set"
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echo ""
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# Create output directory
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mkdir -p figures
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echo "✓ Created figures/ directory"
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echo ""
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# Example 1: Simple flowchart
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echo "Example 1: CONSORT Flowchart"
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echo "----------------------------"
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python scripts/generate_schematic.py \
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"CONSORT participant flow diagram. Assessed for eligibility (n=500). Excluded (n=150) with reasons: age<18 (n=80), declined (n=50), other (n=20). Randomized (n=350) into Treatment (n=175) and Control (n=175). Lost to follow-up: 15 and 10. Final analysis: 160 and 165." \
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-o figures/consort_example.png \
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--iterations 2
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echo ""
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echo "✓ Generated: figures/consort_example.png"
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echo " - Also created: consort_example_v1.png, v2.png, v3.png"
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echo " - Review log: consort_example_review_log.json"
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echo ""
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# Example 2: Neural network (shorter for demo)
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echo "Example 2: Simple Neural Network"
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echo "--------------------------------"
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python scripts/generate_schematic.py \
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"Simple feedforward neural network diagram. Input layer with 4 nodes, hidden layer with 6 nodes, output layer with 2 nodes. Show all connections. Label layers clearly." \
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-o figures/neural_net_example.png \
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--iterations 2
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echo ""
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echo "✓ Generated: figures/neural_net_example.png"
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echo ""
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# Example 3: Biological pathway (minimal)
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echo "Example 3: Signaling Pathway"
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echo "---------------------------"
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python scripts/generate_schematic.py \
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"Simple signaling pathway: Receptor → Kinase A → Kinase B → Transcription Factor → Gene. Show arrows with 'activation' labels. Use different colors for each component." \
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-o figures/pathway_example.png \
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--iterations 2
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echo ""
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echo "✓ Generated: figures/pathway_example.png"
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echo ""
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echo "=========================================="
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echo "All examples completed successfully!"
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echo "=========================================="
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echo ""
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echo "Generated files in figures/:"
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ls -lh figures/*example*.png 2>/dev/null || echo " (Files will appear after running with valid API key)"
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echo ""
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echo "Review the review_log.json files to see:"
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echo " - Quality scores for each iteration"
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echo " - Detailed critiques and suggestions"
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echo " - Improvement progression"
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echo ""
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echo "Next steps:"
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echo " 1. View the generated images"
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echo " 2. Review the quality scores in *_review_log.json"
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echo " 3. Try your own prompts!"
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echo ""
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