Deep-model handoff loop

Deep-model handoff loop

A slow, non-agentic frontier reasoning model is a different tool from your coding agent, and it needs a different workflow. This skill is that workflow.

Written against GPT Pro on the ChatGPT web UI, with the codebase loaded into a Project as split zip bundles (produced by the gptpro export skill). It transfers to any deep model you reach through a chat UI rather than a harness.

The defining fact: the model is non-agentic — no shell, no live filesystem, bounded context. It reasons over a static snapshot.

That drives the entire discipline: it proposes, you verify, then you implement. Its report is the strongest kind of input, but it is read against a snapshot that may lag the live tree, and it cannot run a test. Nothing ships unchecked. In practice the large majority of findings hold up — the job is to catch the ones that don't before they cost you.

What this model is (and how it behaves)

Internalize the model before writing for it. Its constraints and its personality both shape the prompt.

• No harness, no live repo. It runs in the chat provider's own container: no shell, no tools, no filesystem. It sees only the bundled snapshot you upload. On the harness axis it is strictly disadvantaged; its reasoning depth is what makes up for that. You give up "can run a test" to buy "can out-think the problem."
• Slow, deep, one-shot. A single answer can take ~50–60 minutes. You do not iterate cheaply. The prompt must be complete and self-contained, because there is no follow-up channel mid-run.
• The prompt is the entire interface. The agent authors it; the operator copies it verbatim into the web UI. No tool call, no back-channel. What you write is exactly and only what the model gets.
• The operator sets the reasoning tier at send time. NEVER put reasoning-effort instructions in the prompt (no "use xhigh", no <REASONING> block) — that's a UI control, so any such text is dead weight crowding the real instructions.
• Obsessively literal. It follows instructions to the letter and hyper-focuses on exactly what you specify. A superpower for audits, and a