Overview & Result
In long-running agent trajectories, verbose shell outputs and redundant tool results degrade reasoning and blow past context limits. Pi Context Curator scores each history block with Jev, pruning stale noise while preserving critical constraints.
How Jev fits in the loop
- Chunk agent trajectory into distinct conversational turns and tool outputs.
- Pass each chunk through Jev Score against the primary agent mission.
- Classify chunks into Keep, Compress, or Discard categories.
- Reassemble the active context window with only high-relevance items.
How to reproduce
- Integrate Shashank-H/pi-jev-context-curator into an autonomous agent conversation loop.
- Run a long-horizon multi-step task that generates verbose tool call returns.
- Inspect the pruned context window to verify high-signal instruction retention.
Why this build matters
Protects long-horizon agents from hallucinations and quality degradation caused by context window saturation.
Limitations
- Overly aggressive pruning can drop subtle dependencies; requires conservative score thresholds.
- Historical records should be archived to disk/vector store before removal from the active window.
- Does not generate summaries itself; focuses strictly on retention scoring.