Coding Usage

Coding Usage aggregates every local Claude Code and Codex session on your machines into one API-equivalent cost view. Across sessions it totals ( authoritative, estimated), spanning . On a flat subscription you do not actually pay these amounts — the figure answers “what would this have cost on the API”, exactly like Claude Code's own /usage.

Two kinds of cost

Authoritative — for Claude sessions you have opened, the cost is Claude Code's own /usage figure. The status line records it per session to ~/.claude/usage-ledger.json and the report uses it verbatim (no estimation).

Estimated (shown with a leading ~) — older Claude sessions and all Codex sessions have no ledger entry, so their cost is tokens × API list price. Only sessions opened after the status line was configured have an authoritative entry; that is why most rows are estimates.

Per-model breakdown vs. session total

The Cost column is the whole-session total. Expand a row to see every model it used, most expensive first, with that model's tokens and an estimated cost. When the session total is authoritative, the per-model estimates will not sum to exactly the same number — e.g. an authoritative $44.08 next to a per-model subtotal of ~$46.35. That is expected: one is Claude's billed figure, the other is a token-based estimate. It is not a double count.

Models and the <synthetic> marker

Each session lists all models it used. Claude Code's internal <synthetic> entries (locally-generated messages such as interrupts and error notices) carry no tokens and no API call, so they are filtered out — they are not a real model.

Monthly attribution

A session's entire cost is attributed to the month it started. Almost all sessions happen within one day, so this rarely matters; a session that spans a month boundary counts in its start month. Per-day splitting is not done because the authoritative /usage figure is a single session total with no daily breakdown.

Caching

Anthropic bills a cache-write premium (5-minute TTL 1.25×, 1-hour 2×) and cheap cache reads (0.1×). OpenAI has no write surcharge — only a cached-input discount — so Codex cache writes are not charged.

Where the data comes from

Each app writes transcripts to its own home directory, so WSL and Windows are separate locations:

CLI vs Desktop is not a different folder — it is recorded inside each transcript and shown in the Surface column. Cloud / container sessions (Codex Cloud tasks, Claude Code on the web) run server-side and leave no local transcript, so they cannot be measured here.

Multiple devices & privacy

Each machine writes a committed data/<host>.json; this site is rebuilt from those files, and the Device filter narrows totals to one machine. The data holds project names, dates and costs — no secrets — but keep the repo private if that matters.