← Use Cases/Token Context Compression

Active Context Window Compression & Token Optimization

Coding agents send massive context windows containing unmodified files, noisy test outputs, and duplicate logs. ReclaimLLM compresses this context window waste before requests are sent.

📁 Diff-on-Change Read Caching

When coding agents repeatedly read large source files, ReclaimLLM sends structured diffs instead of re-transmitting unchanged file bodies.

🧪 Test Output Filtering

Automatically strips hundreds of passing test lines across pytest, Jest, Vitest, Go, and Cargo, presenting only actionable failures to the model.