A
licenseA
qualityB
maintenanceEnables coding agents to compact conversation contexts verbatim, make fast decisions through choice, boolean, and rubric scoring, and enforce command safety guardrails.
6
MIT
jev-compactor
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AlicenseNot gradedqualityDmaintenanceProvides production-grade context compression for LLM agent conversations with Q-protective ranking, epistemic markers, and semantic store, reducing token usage while preserving equivalence.3Business Source 1.1- AlicenseNot gradedqualityBmaintenanceEnables agents to deterministically shrink multi-turn conversation history and prompts by stripping verbose boilerplate and filler tokens while preserving critical tool parameters and named entities. This lets users cut inference costs by roughly 40-60% without losing essential context, running either as a native MCP server over JSON-RPC stdio or as an importable zero-dependency Python module.7MIT
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