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refactor: don't hardcode model — use codex default (always latest)

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Garry Tan 2026-03-18 21:32:58 -07:00
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2 changed files with 12 additions and 22 deletions
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17
codex/SKILL.md
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@ -410,11 +410,9 @@ Session saved — run /codex again to continue this conversation.
## Model & Reasoning ## Model & Reasoning
**Models** (with ChatGPT login): **Model:** No model is hardcoded — codex uses whatever its current default is (the frontier
- `gpt-5.2-codex` (default) — frontier agentic coding model, best overall agentic coding model). This means as OpenAI ships newer models, /codex automatically
- `gpt-5.2` — deeper reasoning for non-coding analysis uses them. If the user wants a specific model, pass `-m` through to codex.
- `gpt-5.1-codex-max` — deep and fast reasoning, 30% cheaper
- `gpt-5.1-codex-mini` — faster and cheaper, less capable
**Reasoning effort** varies by mode — use the right level for each task: **Reasoning effort** varies by mode — use the right level for each task:
- **Review mode:** `high` — thorough but not slow. Diff review benefits from depth but doesn't need maximum compute. - **Review mode:** `high` — thorough but not slow. Diff review benefits from depth but doesn't need maximum compute.
@ -424,19 +422,16 @@ Session saved — run /codex again to continue this conversation.
**Web search:** All codex commands use `--enable web_search_cached` so Codex can look up **Web search:** All codex commands use `--enable web_search_cached` so Codex can look up
docs and APIs during review. This is OpenAI's cached index — fast, no extra cost. docs and APIs during review. This is OpenAI's cached index — fast, no extra cost.
If the user specifies a model (e.g., `/codex review -m gpt-5.1-codex-max`), If the user specifies a model (e.g., `/codex review -m gpt-5.1-codex-max`
pass the `-m` flag through to codex. or `/codex challenge -m gpt-5.2`), pass the `-m` flag through to codex.
--- ---
## Cost Estimation ## Cost Estimation
Parse token count from stderr. Codex prints `tokens used\nN` to stderr. Parse token count from stderr. Codex prints `tokens used\nN` to stderr.
Estimate cost based on the model:
- gpt-5.2-codex: ~$0.008 per 1K tokens (estimate)
- o3: ~$0.01 per 1K tokens (estimate)
Display as: `Tokens: N | Est. cost: ~$X.XX` Display as: `Tokens: N`
If token count is not available, display: `Tokens: unknown` If token count is not available, display: `Tokens: unknown`

17
codex/SKILL.md.tmpl
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@ -264,11 +264,9 @@ Session saved — run /codex again to continue this conversation.
## Model & Reasoning ## Model & Reasoning
**Models** (with ChatGPT login): **Model:** No model is hardcoded — codex uses whatever its current default is (the frontier
- `gpt-5.2-codex` (default) — frontier agentic coding model, best overall agentic coding model). This means as OpenAI ships newer models, /codex automatically
- `gpt-5.2` — deeper reasoning for non-coding analysis uses them. If the user wants a specific model, pass `-m` through to codex.
- `gpt-5.1-codex-max` — deep and fast reasoning, 30% cheaper
- `gpt-5.1-codex-mini` — faster and cheaper, less capable
**Reasoning effort** varies by mode — use the right level for each task: **Reasoning effort** varies by mode — use the right level for each task:
- **Review mode:** `high` — thorough but not slow. Diff review benefits from depth but doesn't need maximum compute. - **Review mode:** `high` — thorough but not slow. Diff review benefits from depth but doesn't need maximum compute.
@ -278,19 +276,16 @@ Session saved — run /codex again to continue this conversation.
**Web search:** All codex commands use `--enable web_search_cached` so Codex can look up **Web search:** All codex commands use `--enable web_search_cached` so Codex can look up
docs and APIs during review. This is OpenAI's cached index — fast, no extra cost. docs and APIs during review. This is OpenAI's cached index — fast, no extra cost.
If the user specifies a model (e.g., `/codex review -m gpt-5.1-codex-max`), If the user specifies a model (e.g., `/codex review -m gpt-5.1-codex-max`
pass the `-m` flag through to codex. or `/codex challenge -m gpt-5.2`), pass the `-m` flag through to codex.
--- ---
## Cost Estimation ## Cost Estimation
Parse token count from stderr. Codex prints `tokens used\nN` to stderr. Parse token count from stderr. Codex prints `tokens used\nN` to stderr.
Estimate cost based on the model:
- gpt-5.2-codex: ~$0.008 per 1K tokens (estimate)
- o3: ~$0.01 per 1K tokens (estimate)
Display as: `Tokens: N | Est. cost: ~$X.XX` Display as: `Tokens: N`
If token count is not available, display: `Tokens: unknown` If token count is not available, display: `Tokens: unknown`