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You can parse Claude Code compaction logs to analyze token usage by processing session log datasets to compute total tokens used, compaction frequency, and context size trends using PowerShell for deterministic log parsing.

Context compaction timing analysis quantifies how Claude Code uses context by parsing session logs to measure token consumption and context growth, revealing patterns that inform context window management and token budgeting.

Yes, you can use PowerShell to compute context size trends from session logs. It parses compaction logs deterministically to calculate average context size, compaction frequency, and token-usage trends with optional per-category breakdowns.

To quantify Claude Code token consumption and identify usage spikes, run context usage analysis on session log datasets to compare daily context usage and compute total tokens used alongside compaction frequency.

Yes, this context analytics approach supports per-category breakdowns. It parses compaction logs to compute token-usage trends and average context size, allowing you to segment the structured reporting by specific categories.

The best way to measure context window management and token budgeting needs is to analyze compaction timing data from session logs, which identifies patterns in token consumption and context growth to inform optimization strategies.