analyze-usagelisted

# Analyze usage Use when you want to understand your own footprint: how many tokens you're burning, and which installed capabilities are actually pulling their weight. ## Where the data is Claude Code writes a JSON-lines transcript per session at: ``` ~/.claude/projects/<project-hash>/<session-id>.jsonl ``` Each line is one event; assistant turns carry token usage, and tool-use events name the tool or skill invoked. It's local and safe to read. ## Token burn Sum token usage across a session or a day. The fields are nested (`message.usage.input_tokens` / `output_tokens`), so use python for anything beyond a trivial count — don't hand-roll it in a shell one-liner. ## Dead-weight detection (the useful one) 1. List what's installed: `agentstack lib list` (library skills + servers) and the project's active profile. 2. Extract which skills/servers were actually invoked, from the transcripts' tool-use / skill-load events. 3. The set difference — **installed but never invoked** — is dead weight: it taxes every session's context window for nothing. Propose pruning it. ## Rules - **Read-only and local.** Never send transcript content anywhere; report only aggregates — counts, totals, names. - **Best-effort.** The transcript format is undocumented and can change — tolerate unknown lines, don't assume a fixed schema. - **Coverage is uneven.** This is rich for Claude Code; other CLIs expose less (or nothing). Say which agents you could actually see. ## Note age