250 prompts designed to evaluate language models' ability to infer intent and generate complete, fully-featured implementations from minimal instructions. The dataset was created by syntropy-ai and was last updated on 2026-06-22.
Use Cases
- Benchmarking code generation models based on the dataset's 250 prompts
- Evaluating model performance on intent inference from minimal specifications
- Training models to produce complete implementations without requiring clarifying questions
Strengths
- Dataset contains 250 distinct prompts for evaluation
- Focuses on a specific, defined task of generating complete code from minimal prompts
Limitations
- Column-level documentation is absent; field semantics must be inferred after download
- Row count is unknown, which may limit suitability assessment
- Description metadata is limited; actual data quality requires manual inspection after download
Provenance
- Source
- syntropy-ai
- Freshness
- Last updated 2026-06-22 11:22:44; freshness should be verified