Instant Context Compaction

Overview & Result

Long-running coding agents accumulate tool results and history. Jev can judge the relevance of each item against the current task, while ordinary code applies keep, review, and recovery rules.

How Jev fits in the loop

1. Turn the current task and context items into a review state.
2. Score or classify each item's relevance with Jev.
3. Retain uncertain or safety-critical material.
4. Let code compact the context and restore it if later checks fail.

How to reproduce

1. Split an agent history into independently reviewable context items.
2. Ask Jev for bounded relevance or retention judgments against the current task.
3. Keep uncertain items, compare task outcomes before and after compaction, and preserve a recovery path.

Why this build matters

It is a practical example of Jev handling repetitive bounded judgments while the coding agent and context manager retain control of content generation and deletion.

Limitations

• This record is based on a community demonstration, not an independent benchmark.
• Removing the wrong context can silently degrade an agent's next action.
• Summarization, storage, deletion, and restoration are performed by the language model or surrounding code, not Jev.

Patterns