Replace deploy skill environment-variable scan with a script

## Summary

Copilot has identified a portion of a skill that is a good candidate for replacement with a script.

The candidate is the **environment-variable scan** in the `foundry-agent/deploy` skill (`deploy.md`).

## Candidate description

**Environment-variable scan (Step 1)**

A per-language pattern search across source files (currently delegated to a sub-agent). The raw search is deterministic and output-heavy; only the matched variable names matter. A grep/`Select-String` script per language could perform the extraction. Note the *classification* (required vs optional, with default) still needs agent judgment — so a script would cover the search/extraction portion of the step, not the full step.

## Affected file and lines

- [`deploy.md` — Step 1: environment variable scan (L88–L98)](https://github.com/microsoft/GitHub-Copilot-for-Azure/blob/164e0cda7b9d75d6e0d64b235d17bd7ff5e2909e/plugin/skills/microsoft-foundry/foundry-agent/deploy/deploy.md#L88-L98)

## Next steps

1. **Evaluate the candidate** — confirm the steps are stable and parameterizable, and that the script captures everything the skill needs.
2. **Create both a bash _and_ a PowerShell version** of the script so the skill works across platforms.
3. **Run integration tests** to verify the scripts behave correctly and the skill still completes end-to-end.

## Background Information

### Why replace regular steps with scripts

Replacing a regular, well-defined series of steps with a script can:

- **Reduce token usage** — the skill no longer needs to spell out each command and parse large command output inline; the agent invokes one script and reads a compact result.
- **Improve reliability** — the logic is written and tested once, instead of being re-derived by the agent on every run.
- **Improve determinism** — the same inputs always produce the same steps and output, removing run-to-run variation.
- **Improve speed of execution** — a single script call replaces multiple round-trips of command generation, execution, and large-output parsing.

### Authoring notes for the scripts

- **Reference scripts with markdown links**, not just a bare path to the script file.
- **Include examples** in the skill showing how to run each script (sample invocation with arguments).
- **Briefly explain what each script does** where it is referenced.
- **The script output should explain what it did**, so the agent and user can understand the result without re-inspecting raw command output.

Start with deploy.md Step 1, the environment-variable scan at L88–L98, and evaluate whether its search and extraction steps are stable and parameterizable. Create bash and PowerShell versions covering matched variable-name extraction, then run the integration tests to verify end-to-end behavior. Update the skill with linked scripts, invocation examples, and output that explains the result.

Written by the indexing model from the issue text.