Azure · dargilco · Jun 2, 2026 · Jun 2, 2026 · Jun 2, 2026 · Jun 3, 2026
@@ -46,6 +46,15 @@ SHAREPOINT_USER_INPUT=
 FABRIC_USER_INPUT=
 BING_CUSTOM_USER_INPUT=
 A2A_USER_INPUT=
+EVALUATOR_NAME=
+DATASET_NAME=
+DATASET_VERSION=
+POLL_INTERVAL_SECONDS=
+EVAL_MODEL=
+OPTIMIZATION_MODEL=
+JOB_ID=
+WORK_IQ_PROJECT_CONNECTION_ID=
+WORK_IQ_USER_INPUT=
 
 #######################################################################
 #

@@ -7,7 +7,7 @@
   git clone https://github.com/Azure/azure-sdk-for-python.git
   ```
 * Change to the directory `sdk\ai\azure-ai-projects`. 
-* Switch to the current feature branch: `git switch feature/azure-ai-projects/2.2.0`.
+* Switch to the current feature branch, for example: `git switch feature/azure-ai-projects/2.3.0`.
 * Make sure you don't have any files edited or added in this branch (clean `git status` state).
 
 ## Emit from TypeSpec and create a PR
@@ -17,16 +17,26 @@
 * Open VSCode in the current folder.
 * Open the CoPilot chat window ("Toggle Chat").
 * Make sure you are in "Agent" mode.
-* Start typing `/azure-ai-projects` and press tab to auto complete it to `/azure-ai-projects-emit-from-typespec`, then press Enter.
+* Start typing `/` followed by the skill name, like `/azure-ai-projects` and press tab to auto complete it to the designed skill, like `/azure-ai-projects-emit-from-typespec`, then press Enter.
 * Answer some questions and approve execution to go through the workflow
 
 ### Using CoPilot CLI or Agency Copilot CLI
 
 * Install [GitHub CoPilot CLI](https://docs.github.com/copilot/how-tos/copilot-cli/set-up-copilot-cli/install-copilot-cli) or [Agency CoPilot CLI](https://aka.ms/agency) (VPN required) if you don't already have it.
 * Run CoPilot CLI by typing `copilot`
-* Start typing `/azure-ai-projects` and press tab to auto complete it to `/azure-ai-projects-emit-from-typespec`, then press Enter.
+* Start typing `/` followed by the skill name, like `/azure-ai-projects` and press tab to auto complete it to the desired skill, like `/azure-ai-projects-emit-from-typespec`, then press Enter.
 * Answer some questions and approve execution to go through the workflow
 
+## Skills
+
+### azure-ai-projects-emit-from-typespec
+
+This skill creates a new topic branch, emits SDK from TypeSpec, runs some post-processing and creates a PR.
+
+### azure-ai-projects-update-changelog
+
+This skill updates the file CHANGELOG.md, comparing the source in the current branch which the source of the latest public release. It does not create a new topic branch or a PR.
+
 
 
 

@@ -30,11 +30,11 @@ Ask the user the following questions **one at a time**, waiting for each answer
 
 Ask the user to choose **one** of the following two options for the target topic branch:
 
-1. **Create a new topic branch (with default branch name)**  – Create a new topic branch for the emitted changes. If selected, this default branch name will be used "<github-userid>/<emit-from-typespec-DD-MM-HH-MM>", where `github-userid` is the user's GitHub ID and `DD-MM-HHMM` is the current date-time using date, month, hour and minute. For example, if the GitHub ID is "dargilco" and the current date and time is May 1st, 2026 at 8:13am, the default branch name would be `dargilco/emit-from-typespec-01-05-0813`. This should be the default option, and the default branch name should be displayed. If you press enter without typing anything, this option will be selected.
+1. **Create a new topic branch (with default branch name)**  – Create a new topic branch for the emitted changes. If selected, this default branch name will be used "<github-userid>/<emit-from-typespec-DD-MM-HH-MM>", where `github-userid` is the user's personal GitHub ID (not the Microsoft Enterprise Managed User (EMU) account!) and `DD-MM-HHMM` is the current date-time using date, month, hour and minute. For example, if the GitHub ID is "dargilco" and the current date and time is May 1st, 2026 at 8:13am, the default branch name would be `dargilco/emit-from-typespec-01-05-0813`. This should be the default option, and the default branch name should be displayed. If you press enter without typing anything, this option will be selected.
 
-2. **Create a new topic branch (branch name given by user)** - Ask the user for the branch name. Mention that a common format is "<github-userid>/<work-title>". If the user enters a branch name `feature/azure-ai-projects/2.2.0` then stop and report that they cannot emit directly to the current feature branch.
+2. **Create a new topic branch (branch name given by user)** - Ask the user for the branch name. Mention that a common format is "<github-userid>/<work-title>". If the user enters a branch name `feature/azure-ai-projects/2.3.0` then stop and report that they cannot emit directly to the current feature branch.
 
-3. **Emit to current branch** – Emit directly to the current branch without creating a new topic branch. This is not common, but may be necessary if the user is re-running this workflow because of a previous failure, where the topic branch was already created. If the current branch is named `feature/azure-ai-projects/2.2.0` then stop and report that they cannot emit directly to the current feature branch.
+3. **Emit to current branch** – Emit directly to the current branch without creating a new topic branch. This is not common, but may be necessary if the user is re-running this workflow because of a previous failure, where the topic branch was already created. If the current branch is named `feature/azure-ai-projects/2.3.0` then stop and report that they cannot emit directly to the current feature branch.
 
 ### 1b. TypeSpec source
 
@@ -117,13 +117,9 @@ git push -u origin <topic-branch>
 
 ## Step 7: Run post-emitter fixes
 
-After a successful emit, run the post-emitter fix script located in the `sdk/ai/azure-ai-projects` folder:
+After a successful emit, run the PowerShell script named `PostEmitter.ps1` located in the `sdk/ai/azure-ai-projects` folder.
 
-```
-post-emitter-fixes.cmd
-```
-
-This script applies azure-ai-projects-specific corrections to the emitted code (restores `pyproject.toml`, fixes enum names, patches Sphinx doc-string issues, and runs `black` formatting).
+This script applies azure-ai-projects specific corrections to the emitted code (restores `pyproject.toml`, fixes enum names, patches Sphinx doc-string issues, and runs `black` formatting).
 
 **If the script fails**, stop and report the error to the user. Do not continue. Do not attempt to analyze the script failures and fix them with Copilot. The script should be fixed by the engineering team if it is not working.
 
@@ -174,14 +170,16 @@ In the folder `sdk\ai\azure-ai-projects`, run `pip install -e .` to install the
 
 ---
 
-## Step 12: Update CHANGELOG.md
+## Step 12: Run `apiview-stub-generator` to update api.md and api.metadata.yml files
+
+In the root of the `azure-sdk-for-python` folder run the following commands
+
+```
+azpysdk apistub --md --extract-metadata azure-ai-projects --dest-dir .
+```
 
-Use the **`azsdk-common-generate-sdk-locally`** skill's changelog capability (`azsdk_package_update_changelog_content`) to update `CHANGELOG.md` in the `sdk/ai/azure-ai-projects` folder with a summary of changes from the TypeSpec emit. Some guidelines to follow:
-* Start by examining the public SDK API surface of the latest released version of the azure-ai-projects package. The source code for this version can be found in the Main branch of the `azure-sdk-for-python` repository, in the folder `sdk\ai\azure-ai-projects`. 
-* Then compare it to the public SDK API surface of current version in this topic branch. 
-* Look at the existing change log from the latest version (if exists) and edit or add to it to capture all the changes you see. If a change log does not exist for the current version at the top of `CHANGELOG.md`, create a new one.
-* If a new method was added, there is no need to add the list of all new classes that define the inputs and output of the method. It's enough to mention that the new method was added.
-* Show the user the proposed changelog entry and ask for confirmation or edits before saving.
+This will update the `api.md` and `api.metadata.yml` files under in the package folder `sdk\ai\azure-ai-projects`. Now change directory
+back to the package folder.
 
 ---