A developer has created a Python script called `jCodeMunch` to help users understand what is consuming their Claude Code context window. The script analyzes local session logs to identify which tool calls and file reads are contributing the most tokens. This allows users to pinpoint the source of high token usage before making changes, as tool results are sent with every request and can accumulate over a session. AI
IMPACT Helps users optimize Claude Code usage and potentially reduce costs by identifying token-heavy tool interactions.
RANK_REASON The item describes a user-created script for analyzing a specific product's usage.
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