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omp-jev-compaction

jerryfane/omp-jev-compaction

Verbatim omp context reduction scored by Jev, via TypeSafe or OpenRouter.

Automated README summary

Automatically summarized from the README on 25 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

An omp plugin that shrinks conversation context without rewriting it: tool calls and results are scored by Jev, and only low-scoring ones are truncated to a short head plus a recoverable note. All user and assistant text passes through unchanged.

How it uses Jev

Jev scores each tool call and result as a Noul decision over the conversation state (tool names, inputs, message text; outputs replaced by size notes first). Low-probability items are truncated to a head plus a spill-file note; the rest is passed through byte-identical. Decisions are cached and re-applied stickily between rare rewrites.

Primitives:noul

Technique worth stealing

Sticky decision reuse: remember tool_use_id to replacement mappings and re-apply them between rare rewrites so the cached prefix stays byte-identical.

Try it

omp plugin install jerryfane/omp-jev-compaction, then run omp; reduction is on by default.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.14.0
Project signals
jev-1.14.0
Category
jev-1.14.0
Pattern tags
jev-1.14.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectFound in material0.85
  • Shows a System One patternnot found in the excerpt0.14
  • Describes handling uncertaintynot found in the excerpt0.04
  • Reports measured numbersnot found in the excerpt0.02
  • Is a runnable toolFound in material0.87
  • Top-10 learning shortlist signalnot found in the excerpt0.38
  • Is a replica of the modelnot found in the excerpt0.17
  • Solves a common problem (0–2)score on a 0–2 scale1.12 / 2
  • About JevFound in material0.99
Signals
Jev is core to the project0.85Shows a System One pattern0.14Describes handling uncertainty0.04Reports measured numbers0.02Is a runnable tool0.87Top-10 learning shortlist signal0.38Is a replica of the model0.1700.51Solves a common problem (0–2)1.12 / 2012

no-judgment band (0.40–0.60)

Design patterns
Fail open, fail closed0.96Thermostat0.88Questionnaire0.61Traffic light0.60Funnel0.5500.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 25 Oct 2026.