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Show HN: CodeBurn – Analyze Claude Code token usage by task
Built this after realizing I was spending ~$1400/week on Claude Code with almost no visibility into what was actually consuming tokens.<p>Tools like ccusage give a cost breakdown per model and per day, but I wanted to understand usage at the task level.<p>CodeBurn reads the JSONL session transcripts that Claude Code stores locally (~/.claude/projects/) and classifies each turn into 13 categories based on tool usage patterns (no LLM calls involved).<p>One surprising result: about 56% of my spend was on conversation turns with no tool usage. Actual coding (edits/writes) was only ~21%.<p>The interface is an interactive terminal UI built with Ink (React for terminals), with gradient bar charts, responsive panels, and keyboard navigation. There’s also a SwiftBar menu bar integration for macOS.<p>Happy to hear feedback or ideas.
CodeBurn is a timely utility addressing the high costs of AI agent usage, but it currently lacks the defensibility and scale required for venture investment. While the task-level classification is clever, the project faces extreme platform risk as Anthropic could natively integrate these analytics, and the current scope is limited to a single CLI tool.