Claude Code 的 token 實際花在哪裏：7 天日誌顯示工具輸出並非主要成本來源

A few days ago I tested three Claude Code token-saving tools, and all three raised my cost. So this time I stopped testing tools and measured where my cost actually comes from.

How I measured

My local Claude Code session logs, numbers only, 7 days (about 4,400 model calls per day)
Cost-weighted tokens: input 1, cache write 1.25, cache read 0.1, output 5

Where it goes

Where	Share of daily cost
Cache reads (re-reading context every call)	66%
Cache writes	18%
Output	15%

The average call carried about 184K tokens of context. Calls with more than 200K were 56% of the cost.
The median session starts at about 62K tokens before I type anything (system prompt, instructions, tool and skill lists).
Cache breaks cost 6.5%. Three quarters of that came after a gap of more than 60 minutes.
Command output was about 6.8% and file reads 2.6%. That's why compressing tool output didn't help me.
Moving bulk work from subagents to plain scripts cut subagent cost by 78%.
My manager session (the one that coordinates other sessions) costs 11.3% per day. My hooks cost 0.8%.

Replaying my real calls with different habits

Rule	Upper bound	Expected (half, for re-reading)
`/clear` + short handover when context passes 150K	−29.0%	about −14%
Start fresh after a gap of more than 60 minutes	−14.8%	about −7% (overlaps with the above)
Trim the always-loaded context from ~62K to ~32K	−9.4%	about −5%
All three	−42.6%	about −21%

I keep auto-compact off and use /clear with a handover note, because a compacted conversation can't be undone.

Full numbers: https://github.com/awesomefred0827-hash/claude-token-log/blob/main/FINDINGS-2026-10-08.md

Questions

When do you /clear: at a token count, at a task boundary, or after a break?
Has anyone measured how much re-reading a fresh session needs after /clear? That decides whether my "half" assumption is too optimistic.