Enable experiment-driven model selection in smoke-copilot workflow

[Copilot]

New Feature

What does this feature do?

This PR adds a model A/B experiment to an existing agentic workflow and routes a model field through the selected experiment variant. It validates that workflow model selection can be parameterized by experiments.* values.

Why is this feature needed?

We need explicit coverage for experiment-based model assignment to ensure model configuration is not static and can participate in controlled variant rollouts.

Implementation details

• Added model experiment dimension

  Introduced a new experiments.subagent_model variant set in .github/workflows/smoke-copilot.md:

  • small
  • large

• Bound model field to experiment output

  Updated the file-summarizer sub-agent definition to use the experiment-selected model via expression-based assignment.

• Regenerated compiled workflow

  Recompiled smoke-copilot so the generated lock file reflects experiment wiring and runtime expression expansion.

experiments:
  caveman: [yes, no]
  subagent_model: [small, large]

## agent: `file-summarizer`
---
model: ${{ experiments.subagent_model }}
description: Summarizes the content of a file in a few concise sentences
---

[Copilot]

Pull request overview

Adds an experiment dimension to route the smoke Copilot sub-agent model through experiment-selected variants.

Changes:

• Adds subagent_model experiment variants (small, large).
• Updates file-summarizer model selection to reference the selected experiment value.
• Regenerates the compiled workflow lock file with experiment wiring.

Show a summary per file

File	Description
.github/workflows/smoke-copilot.md	Adds the model experiment and wires it into the inline sub-agent definition.
.github/workflows/smoke-copilot.lock.yml	Regenerated workflow reflecting the added experiment outputs and prompt environment bindings.

Copilot's findings

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• Files reviewed: 2/2 changed files
• Comments generated: 1