Compress JSON structures by collapsing large arrays and metadata while preserving error fields. Supports iterative budget-based compression.

Filter and compress raw logs by preserving startup context, shutdown state, and matching error traces while omitting large blocks of repetitive status messages.

Reduce token overhead of MCP tool schemas or JSON Schemas. Strips descriptions/examples (compact mode) or collapses to parameter names/types (minimal mode).

Progressively compress any generic tool response (JSON, HTML, or text) to fit within a specific token budget.

Extract a high-level briefing (goals, decisions, errors, current state, pending tasks) from a conversational message trace (JSON array or raw text) to fit within a token budget.

Normalize dynamic elements like UUIDs, timestamps, and hex IDs to sequential placeholders, maximizing provider-level prompt caching hit rates.

Count tokens using model-aware tokenizers and estimate API costs across multiple configured models.

Generate comparison metrics (token count reduction, compression ratio, cost savings) between uncompressed and distilled text formats.