89 curated builds·evidence labeled
COMMUNITY OBSERVED

Compact Adviser

Evaluates active agent context windows and signals the optimal moment to perform conversation compaction.

Overview & Result

Compacting context too early discards vital reasoning; compacting too late causes token bloat and degraded adherence. Compact Adviser monitors conversation turns to recommend the perfect compaction boundaries.

How Jev fits in the loop

  1. Monitor conversation tokens and tool history turns.
  2. Jev scores context completeness and task closure state.
  3. Trigger automated compaction when confidence exceeds safety threshold.

How to reproduce

  1. Inspect the source implementation at https://github.com/kunchenguid/compact-adviser.
  2. Configure local Jev API credentials and register required tool/model bindings.
  3. Execute test prompts and observe decision latency and routing outputs.

Why this build matters

Prevents context amnesia and maintains sharp agent reasoning in long sessions.

Limitations

  • Metrics are author-reported from the initial release unless independently verified.
  • Requires access to the respective agent framework or runtime environment.
  • Generative model execution remains external to the Jev decision step.

Patterns