Metrics

Codex reports token usage as cumulative totals on its terminal items — the usage object carried by turn.completed. The harness layer reads those totals from the JSON stream and produces the normalized token classes. Aggregation is Last: each usage-bearing line replaces the running total rather than adding to it, so the final reported totals are the ones recorded.

Token classes

The normalized classes are derived from these JSON keys:

Token class	Codex key
Input	input_tokens
Cached input	cached_input_tokens
Output	output_tokens
Reasoning	reasoning_output_tokens

Codex’s input_tokens is inclusive of cached reads (input_includes_cache is true), so the cached input is subtracted from it to yield the uncached input recorded as the uncached input class. Codex has no cache-creation class. Reasoning is reported on its own key (reasoning_output_tokens) and tracked separately from output_tokens, which already excludes it.

Cost

Codex does not self-report a run cost — its usage shape declares no cost field — so there is no harness-reported figure to use. The comparable cost is therefore always OpenRouter-derived: the bare OpenAI model ID is prefixed with openai/ (for example gpt-5.5 becomes openai/gpt-5.5), and the comparable cost is computed from OpenRouter’s listed per-token prices applied to the recorded token classes.

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For how these classes and the comparable cost are defined, see Metrics.