data-storytelling
SkillDev toolsTransform scientific findings into compelling research narratives for papers, grants, and presentations
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the data-storytelling skill
What this skill tells your AI
The instructions your AI receives, as published by lamm-mit/scienceclaw in skills/data-storytelling/SKILL.md and read by ahel’s review.
Overview
Transforms scientific data and findings into compelling research narratives with clear structure, effective framing, and audience-appropriate communication. Generates structured narratives for academic papers, grant applications, conference presentations, and press releases.
Tailors language complexity, emphasis, and structure to the target audience: rigorous and mechanistic for academic peers, accessible and impact-focused for the general public, persuasive and outcomes-oriented for grant reviewers, and concise and punchy for conference abstracts.
Usage
# Generate an academic abstract
python3 skills/data-storytelling/scripts/story_structure.py \
--findings "We identified that BACE1 inhibition reduces amyloid-beta production by 67% in APP transgenic mice, with IC50 of 12 nM and favorable BBB penetration (Kp,uu = 0.8)" \
--audience academic \
--format abstract
# Generate a grant introduction
python3 skills/data-storytelling/scripts/story_structure.py \
--findings "Novel kinase inhibitor reduces tumor growth 80% in xenograft model, 5x selectivity vs off-targets, oral bioavailability 65%" \
--audience grant \
--format introduction
# Generate a press release for public communication
python3 skills/data-storytelling/scripts/story_structure.py \
--findings "Machine learning model predicts drug side effects with 94% accuracy using protein interaction data" \
--audience general \
--format press-release
# Generate a conference discussion section
python3 skills/data-storytelling/scripts/story_structure.py \
--findings "Cryo-EM structure reveals allosteric site 25 Angstrom from active site, explaining cooperative binding" \
--audience conference \
--format discussion
Output Format
{
"audience": "academic",
"format": "abstract",
"narrative": "Background: Alzheimer's disease affects...\n\nObjective: To determine...\n\nMethods: Using computational screening...\n\nResults: We identified...\n\nConclusion: These findings suggest...",
"key_messages": [
"BACE1 inhibition reduces amyloid-beta by 67%",
"IC50 of 12 nM demonstrates high potency",
"BBB penetration confirmed for CNS delivery"
],
"word_count": 187
}
Signals
- GitHub stars
- 242
- Forks
- 42
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
data-storytelling-lamm-mit- Source
- github.com/lamm-mit/scienceclaw