Use case
Developers running DeepSeek Harness-style coding agents need to inspect, after long sessions or compaction/pruning events, what the current context holds, how it is composed, and what was dropped, so they can explain why the agent forgot key facts and decide what to re-supply.
Today users read raw session logs, estimate from token counts, or repeatedly restate requirements to make the agent remember; none of these reconstruct context composition or the specific compaction and pruning actions.
After compaction or pruning in long sessions, the agent silently loses key facts; users see wrong output but not the loss event. Existing harnesses expose session telemetry but not context composition or evolution, so debugging is guesswork.
xOcto's call
Demand is evidenced
The trend is people needing to see an AI's working memory, or long chats fail silently. The entry is long writing, contracts, and code, where context must be watched, as a ledger a person can read. Judgment: a dashboard is hard to sell alone; pair it with an alert when context is full.
Reason to use it
Why users would choose it
Inference: versus reading logs and restating requirements, the plugin's Context panel and command surface composition, evolution, and compaction/pruning events directly, turning 'guess what was lost' into 'see which step lost it', so developers debugging long sessions open it when the agent starts forgetting.
Where the easy answer breaks down
The tension worth following
An English validation note will follow from the public evidence.
If this is your job
Worth trying. Inference: versus reading logs and restating requirements, the plugin's Context panel and command surface composition, evolution, and compaction/pruning events directly, turning 'guess what was lost' into 'see which step lost it', so developers debugging long sessions open it when the agent starts forgetting.
Entry and what to borrow
The trend is people needing to see an AI's working memory, or long chats fail silently. The entry is long writing, contracts, and code, where context must be watched, as a ledger a person can read. Judgment: a dashboard is hard to sell alone; pair it with an alert when context is full.