Usage Data — Data skill for Claude Code

usage-data

Public, auto-refreshed data file powering [maxghenis.com/usage](https://maxghenis.com/usage).

`usage.json` is regenerated every ~30 minutes by `build_usage.py` + `extract.py`, which read the raw Claude Code and Codex session JSONL on my machine and aggregate to daily totals. Only daily aggregates are published: token counts, computed cost at public API list prices, and model breakdowns. No message content, no file paths, no project names.

Methodology

• Dated to when usage happened. Every API call is bucketed by its own timestamp (UTC), not by session start, so sessions that span weeks don't pile onto their start date.
• Bill-faithful codex accounting. Codex fork/resume writes a snapshot file containing a full replay of prior history under a fresh session id. Replays are detected structurally — the leaf session_meta (carrying forked_from_id) adjacent to the copied ancestor's session_meta, with the native boundary at the first task_started whose preserved started_at agrees with its own outer timestamp — never by wall-clock timing, which misses multi-second copied prefixes and falsely discards fresh same-second work. Genuine cumulative-counter resets segment a file into billing epochs that are summed; rate-limit-only heartbeats are ignored. Only live continuation deltas of total_token_usage count.
• Claude requests deduplicated globally by (message.id, requestId) with the last occurrence winning: subagent transcripts stream several usage snapshots per request (the first is a placeholder with output_tokens≈1; the last carries the billed totals), and resumed sessions copy history verbatim into new transcript files.
• Cache-creation captured. Claude prompt-cache writes are priced at the 5m/1h write rates; cache reads at the cache-hit rate.
• Pricing is pinned per model at public list prices (standard tier, no Batch/Flex/long-context modifiers), cross-checked against LiteLLM's