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Sidechain Rate

Agent Behavior

13 PRs with data in past 30d (29 total)

Count
13
Average
17%
↑ 2% vs prior 30d
P10
11%
↑ 6% vs prior 30d
P50
18%
↓ 1% vs prior 30d
P90
23%
↓ 1% vs prior 30d

Trend

Distribution

0–10%
1
10–20%
6
20–30%
6

Notable PRs

Highest
#248Fix table sort state persistence25%
#160Add dark mode support to settings23%
#220Refactor notification preferences23%
Lowest
#196Add custom domain support3%
#176Refactor error boundary hierarchy11%
#244Refactor API client error handling12%

About This Metric

Sidechain Rate

What It Measures

The fraction of messages in a session that occurred on sidechain branches — alternate reasoning paths the model explored and then abandoned. Sidechain messages represent work the model did that didn't contribute to the final output.

Why It Matters

When Claude Code backtracks, it creates sidechain branches — invisible to the user but consuming tokens and time. A high sidechain rate means the model is frequently going down wrong paths before finding the right approach. This is a direct measure of wasted effort.

Tracking sidechain rate helps identify tasks or prompting patterns that confuse the model. If certain types of requests consistently produce high sidechain rates, that's a signal to improve prompt clarity, provide better context via CLAUDE.md, or break the task into smaller pieces.

How It's Calculated

sidechain_rate = sidechain_messages / (human_messages + assistant_messages)

Summed across all sessions correlated to the PR. Returns a value between 0.0 and 1.0. Returns null if there are no messages.

Data Sources Required

  • Claude Code session data — Message-level isSidechain flag from session JSONL files.