What your LLM usage would cost at every seller

#!/usr/bin/env python3
"""Claude Code token usage per model and month, from its own logs on this computer. Prints totals only.
easiapiai.com/bill. Rules (checked against real logs and the open-source ccusage, 2026-10-20):
- every *.jsonl under the projects folders, sub-agent folders included (they are not repeated in the parent);
- only lines with type "assistant"; skip model "<synthetic>";
- one API response appears on several lines (one per content block): key (message.id, requestId) across all
  files, keep the line with the largest token total (output grows from line to line);
- input_tokens excludes cache reads and writes; thinking is part of output_tokens."""
import datetime, glob, json, os, sys
from collections import defaultdict

home = os.path.expanduser("~")
roots = [os.path.join(home, ".claude", "projects"), os.path.join(home, ".config", "claude", "projects")]
roots += [os.path.join(p.strip(), "projects") for p in os.environ.get("CLAUDE_CONFIG_DIR", "").split(",") if p.strip()]
best = {}
for root in dict.fromkeys(roots):
    for path in glob.glob(os.path.join(root, "**", "*.jsonl"), recursive=True):
        with open(path, encoding="utf-8", errors="replace") as fh:
            for line in fh:
                if '"assistant"' not in line:
                    continue
                try:
                    d = json.loads(line)
                except ValueError:
                    continue
                m = d.get("message") if d.get("type") == "assistant" else None
                u, model = (m or {}).get("usage"), (m or {}).get("model")
                if not u or not model or model == "<synthetic>":
                    continue
                cc = u.get("cache_creation") or {}
                w5, w1 = cc.get("ephemeral_5m_input_tokens"), cc.get("ephemeral_1h_input_tokens")
                if w5 is None and w1 is None:
                    w5, w1 = u.get("cache_creation_input_tokens") or 0, 0
                row = (u.get("input_tokens") or 0, u.get("output_tokens") or 0,
                       u.get("cache_read_input_tokens") or 0, w5 or 0, w1 or 0)
                try:
                    month = datetime.datetime.fromisoformat(d["timestamp"].replace("Z", "+00:00")).astimezone().strftime("%Y-%m")
                except (KeyError, ValueError, AttributeError):
                    month = "unknown"
                key = (m.get("id"), d.get("requestId")) if m.get("id") else (path, line)
                if key not in best or sum(row) > sum(best[key][2]):
                    best[key] = (model, month, row)
tot = defaultdict(lambda: [0, 0, 0, 0, 0])
for model, month, row in best.values():
    t = tot[(model, month)]
    for i, v in enumerate(row):
        t[i] += v
usage = [{"model": mo, "label": mn, "input_tokens": t[0], "output_tokens": t[1], "cached_input_tokens": t[2],
          "cache_write_tokens": t[3], "cache_write_1h_tokens": t[4]} for (mo, mn), t in sorted(tot.items())]
json.dump({"usage": usage, "current_seller": "Anthropic"}, sys.stdout, indent=1)
print()