generate-synthetic-data
CommunityCreate diverse synthetic test inputs.
Software Engineering#prompt engineering#llm evaluation#synthetic data#test data generation#data augmentation#data diversity
Authorhamelsmu
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill generates diverse, realistic test inputs for LLM pipelines when real user data is sparse or to stress-test specific failure hypotheses.
Core Features & Use Cases
- Dimension-Based Generation: Creates synthetic data by combining predefined dimensions (axes of variation) and their values.
- Iterative Refinement: Guides users through defining dimensions, drafting tuples, and converting them into natural language queries.
- Use Case: Bootstrapping an evaluation dataset for a new customer support chatbot by generating varied user queries covering different intents and user personas.
Quick Start
Use the generate-synthetic-data skill to create 100 diverse traces for your LLM pipeline.
Dependency Matrix
Required Modules
None requiredComponents
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: generate-synthetic-data Download link: https://github.com/hamelsmu/evals-skills/archive/main.zip#generate-synthetic-data Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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