scientific-generation

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

IndexedMIT★ 1,019

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/beita6969-scientific-generation

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About

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

Use cases: research

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Install scripts: None found

Network hosts it talks to 1

codeload.github.com · found in install command

Files it touches

~/.claude/skills/scientific-generation

What's inside

Skill name: scientific-generation
Description: Generate scientific code, protocols, and domain-specific text with quality control
License: MIT
Instructions: 30 lines in SKILL.md · view on GitHub

Files (1)

SKILL.md

SKILL.md (first lines)

# 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

From beita6969/ScienceClaw, MIT.

Signals

Stars: 1,019
Forks: 109
Open issues: 1
Last commit (this folder): Mar 12, 2026 (7 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License: MIT
Repository: github.com/beita6969/ScienceClaw
Website: scienceclaw.science
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: GitHub github-graphql

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Cite this page

scientific-generation skill. Agent Mart. https://agentmart.dev/skills/beita6969-scientific-generation (last updated 2026-10-24)