Replace azure-prepare skill two-phase azd provision/deploy sequence 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 **two-phase azd provision → deploy sequence (with env-name slug derivation)** in the `azure-prepare` skill, duplicated across six template/recipe files under `references/services/`.

## Candidate description

The skill repeatedly hand-writes the same deterministic deployment sequence to stand up an azd-based project:

1. **Derive a slug environment name** from the working directory — bash: `basename "$PWD" | tr '[:upper:]' '[:lower:]' | tr ' _' '-'` + `-dev`; PowerShell: `Split-Path -Leaf (Get-Location)` lowercased with `[ _]` → `-` + `-dev`.
2. **Initialize non-interactively** — `azd init -t -e "$ENV_NAME" --no-prompt`.
3. **Set location** — `azd env set AZURE_LOCATION `.
4. **Provision, wait, then deploy** — `azd provision --no-prompt` → `sleep 60` (RBAC propagation) → `azd deploy --no-prompt`. (Some call sites use the `azd up --no-prompt` shorthand for the same two phases.)

This is a strong script candidate because it is:
- **Repeated across 6 files** — identical logic copy-pasted in `web-api.md`, `web-app.md`, `recipes/composition.md`, `recipes/README.md`, the Functions `recipes/composition.md`, and the Functions `templates/README.md`. Each copy is maintained in parallel bash + PowerShell variants and drifts independently.
- **Deterministic** — a fixed command sequence with no branching that requires judgment.
- **Order-sensitive and error-prone manually** — the `provision → sleep 60 (RBAC) → deploy` ordering is a documented reliability pattern (skipping the wait causes deploy-time RBAC failures), and the slug derivation differs subtly between shells and is easy to mistype.

**Sketch — `azd-provision-deploy.{sh,ps1}`:**
- **Input:** template name, region, optional explicit env name (defaults to the derived slug).
- **Output:** a compact, self-describing result — the env name used and a clear "provisioned then deployed" confirmation — so the agent does not re-derive the slug or re-parse azd output. A flag can select the single-phase `azd up` shorthand vs. the explicit `provision → sleep → deploy` form.

## Affected file and lines

- [`app-service/templates/web-api.md` — Deployment, bash + PowerShell (L162–L174)](https://github.com/microsoft/GitHub-Copilot-for-Azure/blob/3890cbfb65c548ce8daa96cabd1d8de63f7bbcca/plugin/skills/azure-prepare/references/services/app-service/templates/web-api.md#L162-L174)
- [`app-service/templates/web-app.md` — Deployment, bash + PowerShell (L162–L174)](https://github.com/microsoft/GitHub-Copilot-for-Azure/blob/3890cbfb65c548ce8daa96cabd1d8de63f7bbcca/plugin/skills/azure-prepare/references/services/app-service/templates/web-app.md#L162-L174)
- [`app-service/templates/recipes/composition.md` — Step 1 slug + init (L30–L32)](https://github.com/microsoft/GitHub-Copilot-for-Azure/blob/3890cbfb65c548ce8daa96cabd1d8de63f7bbcca/plugin/skills/azure-prepare/references/services/app-service/templates/recipes/composition.md#L30-L32)
- [`app-service/templates/recipes/composition.md` — Step 7 provision/sleep/deploy (L120–L127)](https://github.com/microsoft/GitHub-Copilot-for-Azure/blob/3890cbfb65c548ce8daa96cabd1d8de63f7bbcca/plugin/skills/azure-prepare/references/services/app-service/templates/recipes/composition.md#L120-L127)
- [`app-service/templates/recipes/README.md` — How It Works, init + provision/sleep/deploy (L38, L58–L61)](https://github.com/microsoft/GitHub-Copilot-for-Azure/blob/3890cbfb65c548ce8daa96cabd1d8de63f7bbcca/plugin/skills/azure-prepare/references/services/app-service/templates/recipes/README.md#L38-L61)
- [`functions/templates/recipes/composition.md` — Deployment Strategy provision/sleep/deploy (L207–L215)](https://github.com/microsoft/GitHub-Copilot-for-Azure/blob/3890cbfb65c548ce8daa96cabd1d8de63f7bbcca/plugin/skills/azure-prepare/references/services/functions/templates/recipes/composition.md#L207-L215)
- [`functions/templates/README.md` — Step 5 env set + up (L79–L82), fallback up (L169)](https://github.com/microsoft/GitHub-Copilot-for-Azure/blob/3890cbfb65c548ce8daa96cabd1d8de63f7bbcca/plugin/skills/azure-prepare/references/services/functions/templates/README.md#L79-L82)

## 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 the deployment sections in the six affected files under plugin/skills/azure-prepare/references/services/, especially the linked line ranges, and compare their bash and PowerShell sequences. Define the script inputs and output from the candidate description, then update the markdown references with examples. Done means both scripts work across the documented flows and integration tests confirm the skill still completes end to end.

Written by the indexing model from the issue text.