open-compress/claw-compactor

Health v2 · maintenance only

Adoption not part of the score

2033 stars · 185 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Claw Compactor is an open-source Python library and CLI tool that compresses LLM input tokens via a 14-stage Fusion Pipeline, achieving 15-82% reduction with zero LLM inference cost. It uses reversible compression, AST-aware code analysis via tree-sitter, and intelligent content routing to shrink prompts and agent context windows.

Use cases

• compress prompts before sending to an LLM to cut token costs
• shrink agent context windows so long sessions fit the model's limit
• compress code workspaces with AST-aware analysis before LLM calls
• reduce token usage in Claude Code or Cursor agent traces
• deduplicate and prune repetitive context in chatbot pipelines
• reversibly decompress content after LLM processing

When to choose

• you want deterministic, offline token compression with no LLM inference cost
• you need reversible compression so original content can be restored
• your workload includes source code that benefits from AST-aware analysis
• you want a Python library plus CLI with MIT licensing and active test coverage

When to avoid

• you need semantic compression that requires an LLM or embedding model
• your prompts are already short and pre-optimized (minimal impact expected)
• you need a hosted gateway that compresses output tokens across providers
• you require guaranteed lossless fidelity for all content types

Facets

library · maturity active

compression nlp parser developer-tools large-language-models artificial-intelligence developer-tools python cli cross-platform token-compression context-window-optimization prompt-compression ast-analysis tree-sitter llm-cost-reduction fusion-pipeline reversible-compression ai-agents natural-language-processing

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