PromptSmith
TARGET: Cursor Composer / Claude 3.5 Sonnet
Reduce Cursor Composer Prompt Tokens by 35%
Conversational filler tokens like "could you please" burn 35% of self-attention compute. PromptSmith decomposes draft instructions into high-density structured contracts in zero milliseconds.
Raw Input Draft
Natural English
High-Density Prompt Output
-38% Tokens Saved
### Problem Specification
Implement a streaming CSV parser in Python with robust error handling and structured logging.
### Invariant & Boundary Criteria
- Stream processing with O(1) memory footprint for multi-gigabyte CSV files.
- Fail-safe handling for malformed rows, missing fields, and type coercion.
- Structured logging outputting execution elapsed time and row drop counters.
### Acceptance Verification Assertions
- Unit tests verifying clean parsing, malformed row recovery, and aggregate correctness.