Theo's approach to running GPT-5.5 as a Claude Code subagent

CLAUDE.md

(stolen from Theo Browne)

Rankings, higher = better. Cost reflects what I actually pay (OpenAI is near-free for me due to a deal), not list price. Intelligence is how hard a problem you can hand the model unsupervised. Taste covers UI/UX, code quality, API design, and copy.

model	cost	intelligence	taste
gpt-5.5	9	8	5
sonnet-5	5	5	7
opus-4.8	4	7	8
fable-5	2	9	9

How to apply:

• These are defaults, not limits. You have standing permission to override them: if a cheaper model's output doesn't meet the bar, rerun or redo the work with a smarter model without asking. Judge the output, not the price tag. Escalating costs less than shipping mediocre work.
• Cost is a tie-breaker only; when axes conflict for anything that ships, intelligence > taste > cost.
• Don't let cost prevent you from using the right model for the job. Instead, take advantage of cheaper options to get more information and try things before moving the work to a more expensive option.
• Bulk/mechanical work (clear-spec implementation, data analysis, migrations): gpt-5.5 — it's effectively free.
• Anything user-facing (UI, copy, API design) needs taste ≥ 7.
• Reviews of plans/implementations: fable-5 or opus-4.8, optionally gpt-5.5 as an extra independent perspective.
• Never use Haiku.
• Mechanics: gpt-5.5 is only reachable through the Codex CLI — codex exec / codex review (my ~/.codex/config.toml defaults to gpt-5.5). Use the codex-implementation, codex-review, and codex-computer-use skills; for work they don't cover (investigation, data analysis), run codex exec -s read-only directly with a self-contained prompt.
• Claude models (sonnet-5, opus-4.8, fable-5) run via the Agent/Workflow model parameter. Using gpt-5.5 inside workflows and subagents (the model parameter only takes Claude models, so use a wrapper):
• Spawn a thin Claude wrapper agent with model: 'sonnet', effort: 'low' whose prompt instructs it to write a self-contained codex prompt, run codex exec via Bash, and return the report (use schema on the wrapper to get structured output back).
• Always label these agents with a gpt-5.5: prefix, e.g. {label: 'gpt-5.5:review-auth'} — the workflow UI shows the wrapper's Claude model, so the label is the only indication the real worker is gpt-5.5.
• Codex runs can exceed Bash's 10-minute timeout: pass an explicit timeout, or run in the background and poll for the report file.
• Parallel gpt-5.5 implementation agents must use isolation: 'worktree' so codex edits don't collide in the shared checkout.
• Workflow token budgets only count Claude tokens; codex work is free and invisible to budget.spent().

@jacobparis it would be amazing to update this with gpt-5.6-* models 🙏