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Claude Code users can now track token usage with jCodeMunch script

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.

Read on dev.to — Claude Code tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Claude Code users can now track token usage with jCodeMunch script

How we ranked this

Signal score
34 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
The item describes a user-created script for analyzing a specific product's usage.
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
product, infra
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AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. dev.to — Claude Code tag TIER_1 English(EN) · J. Gravelle ·

    What's actually filling your Claude Code session? Count the tool results.

    <p>If you're hitting your Claude Code limit faster than seems reasonable, find out which tool put the most text into the session before you change anything. The session log is on your own disk, a short script will rank it for you, and the answer is often not the thing you were ab…