Agent skill · AI & Agents

ml-materials-predictor

Machine learning skill for nanomaterial property prediction and discovery acceleration

a5c-ai1,642★ · 1 repos on radarProfile →
claude-codecodexcan modify filesMIT
Install
npx skills add a5c-ai/babysitter --skill ml-materials-predictor --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 2 KB
Bundled scripts: none
Allowed tools: -Read-Write-Glob-Grep-Bash
Path: library/specializations/domains/science/nanotechnology/skills/ml-materials-predictor/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,642
Language: JavaScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# ML Materials Predictor ## Purpose The ML Materials Predictor skill provides machine learning capabilities for accelerated nanomaterial discovery and property prediction, enabling data-driven approaches to materials design and optimization. ## Capabilities - Feature engineering for materials - Property prediction models (GNN, transformers) - Active learning for experiment design - High-throughput virtual screening - Synthesis success prediction - Transfer learning for small datasets ## Usage Guidelines ### ML Materials Workflow 1. **Data Preparation** - Collect and curate dataset - Generate features (composition, structure) - Handle missing values 2. **Model Development** - Select appropriate architecture - Train with cross-validation - Evaluate on held-out test 3. **Application** - Screen candidate materials - Prioritize experiments - Validate predictions ## Process Integration - Machine Learning Materials Discovery Pipeline - Structure-Property Correlation Analysis ## Input Schema ```json { "dataset_file": "string", "target_property": "string", "model_type": "random_forest|gnn|cgcnn|megnet", "features": "composition|structure|both", "task": "train|predict|screen" } ``` ## Output

What's inside
Steps it walks through
  1. Purpose
  2. Capabilities
  3. Usage Guidelines
  4. ML Materials Workflow
  5. Process Integration
  6. Input Schema
  7. Output Schema
More from babysitter
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About this skill
What does the ml-materials-predictor skill do?

Machine learning skill for nanomaterial property prediction and discovery acceleration

How do I install it?

Run `npx skills add a5c-ai/babysitter --skill ml-materials-predictor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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