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ProductionTracked since May 18, 2026

entire review gains live JSONL agent-event streaming

`entire review` in v0.6.2 now exposes live multi-agent progress and failure signals through JSONL output, making review execution more observable instead of only showing results at the end of a run.

entire reviewJSONL outputagent eventsmulti-agent review

What Happened

  • `entire review` in v0.6.2 now exposes live multi-agent progress and failure signals through JSONL output, making review execution more observable instead of only showing results at the end of a run.
  • `entire review` in v0.6.2 now exposes live multi-agent progress and failure signals through JSONL output, making review execution more observable instead of only showing results at the end of a run.
  • 1 evidence item attached for review.

What is Different

Before

Scattered source updates, isolated context, and manual follow-up across multiple feeds.

Now

Added real-time JSONL event streaming for `entire review` and updated review execution feedback so progress and failure outcomes are surfaced continuously during a run.

Why Track This

Why It Matters

Developers and automation operators using `entire review` can monitor long review sessions as they execute, so failures and stalls are visible earlier and teams can intervene before wasting time on a full, unproductive cycle; this reduces uncertainty in CI workflows and lowers the cost of debugging long checks, but teams should watch for log parser compatibility, increased event volume in downstream tooling, and whether the expanded default scope (including uncommitted changes) changes review signal-to-noise.

Impact

Developers and automation operators using `entire review` can monitor long review sessions as they execute, so failures and stalls are visible earlier and teams can intervene before wasting time on a full, unproductive cycle; this reduces uncertainty in CI workflows and lowers the cost of debugging long checks, but teams should watch for log parser compatibility, increased event volume in downstream tooling, and whether the expanded default scope (including uncommitted changes) changes review signal-to-noise.

What To Watch Next

  • Watch whether entire review becomes a repeated pattern.
  • Track follow-up changes around AI Code Review.
  • Compare future signals against this evidence trail.
  • Re-check risk flags: jsonl_event_parser_breakage, streamed_event_volume_spike.
Open Topic TimelineOpen Technical EventOpen Original Sourcejsonl_event_parser_breakage / streamed_event_volume_spike / default_scope_changes_side_effects / failure_reporting_false_positives

Supporting Evidence