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Analyze Claude Code session data from ~/.claude/projects/ to surface usage patterns, heavy sessions, and context-limit problems.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
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| name | session-stats |
| description | Analyze Claude Code session data from ~/.claude/projects/ to surface usage patterns, heavy sessions, and context-limit problems. |
Run the script next to this file and interpret what comes back:
python3 scripts/session_stats.py
When installed as a plugin the path is ${CLAUDE_PLUGIN_ROOT}/skills/session-stats/scripts/session_stats.py. It reads every .jsonl under ~/.claude/projects/, needs no arguments, and works on any machine — it resolves the home directory itself.
The one thing that trips people up: total tokens is dominated by cache reads, which are re-counted on every assistant turn. A session showing hundreds of millions of "tokens" was not billed at that scale and did not process that much unique text — it means a large context was re-read many times. Output tokens and message count are the honest measures of how much work a session actually did; the total is best used as a relative signal of context weight, comparing sessions against each other rather than against an absolute number.
With that in mind, give the user a real read of their data rather than a restatement of the table:
Then suggest fixes that follow from what you actually saw. Sessions that balloon in context usually want /clear at natural task boundaries or /compact before auto-compaction fires. Heavy cache-creation relative to peers points at a large always-loaded CLAUDE.md. Many tool calls per session points at verbose operations worth delegating to subagents. Very long single sessions are usually less effective than several focused ones — say so when the data shows it, and skip it when it doesn't.