scientific-generation

Generate scientific code, protocols, and domain-specific text with quality control

564 stars

Best use case

scientific-generation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Generate scientific code, protocols, and domain-specific text with quality control

Teams using scientific-generation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/scientific-generation/SKILL.md --create-dirs "https://raw.githubusercontent.com/beita6969/ScienceClaw/main/skills/scientific-generation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/scientific-generation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How scientific-generation Compares

Feature / Agentscientific-generationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Generate scientific code, protocols, and domain-specific text with quality control

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Scientific Generation & Writing

## Purpose
Generate high-quality scientific code, experimental protocols, and domain-specific text outputs.

## Key Datasets
- **Tiny-Codes** (nampdn-ai/tiny-codes): 1.6M code snippets across 11 languages (Python, TypeScript, JavaScript, Ruby, Rust, C++, Java, Go, etc.) for code generation benchmarks
- **Mental Health Counseling** (Amod/mental_health_counseling_conversations): Therapeutic conversation corpus for empathetic response generation

## Generation Types
- **Code generation**: Scientific computing scripts, data pipelines, analysis workflows
- **Protocol generation**: Experimental procedures, assay protocols, clinical workflows
- **Report generation**: Lab reports, progress reports, technical memos
- **Response generation**: Literature-based answers, educational explanations

## Protocol
1. **Requirements analysis** — Define output specifications, constraints, and quality criteria
2. **Template selection** — Choose appropriate template or structure
3. **Content generation** — Generate with domain-specific knowledge
4. **Quality validation** — Check correctness, completeness, and adherence to standards
5. **Iteration** — Refine based on validation feedback

## Rules
- Generated code must include error handling and documentation
- Scientific protocols must specify reagents, equipment, and safety precautions
- All generated content must be factually grounded
- Flag any assumptions or simplifications made during generation
- For therapeutic/counseling contexts, follow ethical guidelines

Related Skills

scientific-writing

564
from beita6969/ScienceClaw

Assist with scientific paper writing, LaTeX formatting, abstract drafting, review responses, grant proposals, and academic communication. Use when user asks to write/edit a paper section, draft an abstract, format in LaTeX, respond to reviewer comments, write a grant proposal, or improve academic writing. Triggers on "write abstract", "draft introduction", "LaTeX", "reviewer response", "grant proposal", "improve my writing", "paper draft", "methods section".

scientific-visualization

564
from beita6969/ScienceClaw

Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.

scientific-summarization

564
from beita6969/ScienceClaw

Summarize and simplify scientific literature, educational content, and research papers

scientific-slides

564
from beita6969/ScienceClaw

Build slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.

scientific-schematics

564
from beita6969/ScienceClaw

Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.

scientific-retrieval

564
from beita6969/ScienceClaw

Retrieve and recommend relevant documents from financial, historical, and scientific archives

scientific-reasoning

564
from beita6969/ScienceClaw

Mathematical and physical reasoning with formal proof construction and problem solving

scientific-problem-selection

564
from beita6969/ScienceClaw

This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".

scientific-prediction

564
from beita6969/ScienceClaw

Predict material properties, economic indicators, and scientific outcomes using computational models

scientific-manuscript

564
from beita6969/ScienceClaw

COPYRIGHT NOTICE

scientific-diagram-generation

564
from beita6969/ScienceClaw

No description provided.

scientific-critical-thinking

564
from beita6969/ScienceClaw

Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.