Repo sync

.github/workflows/needs-sme-stale-check.yaml

@@ -29,8 +29,9 @@ jobs:
           stale-pr-message: 'This is a gentle reminder for the docs team that this PR is waiting for technical review by a subject matter expert.'
           stale-pr-label: 'Waiting on SME review'
           days-before-pr-close: -1 # never close
-          staled-issues-prs: true # report issues and PRs that were commented on as stale in the output
-          closed-issues-prs: true # report issues and PRs that were closed in the output - should always be `0` for this workflow
+
+      - name: Print outputs
+        run: echo "Staled issues/PRs:${{ steps.stale.outputs.staled-issues-prs || '0' }}, Closed issues/PRs:${{ steps.stale.outputs.closed-issues-prs || '0' }}"
 
       - name: Check out repo
         if: ${{ failure() }}

.github/workflows/no-response.yaml

@@ -52,8 +52,8 @@ jobs:
             if you have the information we requested, or open an [issue](https://github.com/github/docs/issues/new/choose)
             to describe your changes. Then we can reopen this PR and begin the review process.
 
-          staled-issues-prs: true # report issues and PRs that were commented on as stale in the output
-          closed-issues-prs: true # report issues and PRs that were closed in the output
+      - name: Print outputs
+        run: echo "Staled issues/PRs:${{ steps.stale.outputs.staled-issues-prs || '0' }}, Closed issues/PRs:${{ steps.stale.outputs.closed-issues-prs || '0' }}"
 
       - name: Check out repo
         if: ${{ failure() }}

.github/workflows/stale.yml

@@ -7,10 +7,14 @@ name: Stale check for stalled pull requests in the docs-internal repository
 on:
   schedule:
     - cron: '20 16 * * 1' # Run each Monday at 16:20 UTC / 8:20 PST
+  push:
+    paths:
+      - .github/workflows/stale.yml
 
 permissions:
   contents: read
   pull-requests: write
+  issues: write
 
 jobs:
   stale:
@@ -28,8 +32,9 @@ jobs:
           close-pr-label: 'Closed as inactive'
 
           operations-per-run: 150
-          staled-issues-prs: true # report PRs that were commented on as stale in the output
-          closed-issues-prs: true # report PRs that were closed in the output
+
+      - name: Print outputs
+        run: echo "Staled PRs:${{ steps.stale.outputs.staled-issues-prs || '0' }}, Closed PRs:${{ steps.stale.outputs.closed-issues-prs || '0' }}"
 
       - name: Check out repo
         if: ${{ failure() }}

.github/workflows/triage-stale-check.yml

@@ -67,8 +67,8 @@ jobs:
           stale-pr-message: 'This is a gentle reminder for the docs team that this pull request is waiting for review.'
           stale-pr-label: 'Waiting on Docs team review'
 
-          staled-issues-prs: true # report issues and PRs that were commented on as stale in the output
-          closed-issues-prs: true # report issues and PRs that were closed in the output
+      - name: Print outputs
+        run: echo "Staled issues/PRs:${{ steps.stale.outputs.staled-issues-prs || '0' }}, Closed issues/PRs:${{ steps.stale.outputs.closed-issues-prs || '0' }}"
 
       - name: Check out repo
         if: ${{ failure() }}

content/actions/concepts/runners/about-actions-runner-controller.md

@@ -2,7 +2,6 @@
 title: About Actions Runner Controller
 shortTitle: About ARC
 intro: 'You can host your own runners and customize the environment used to run jobs in your {% data variables.product.prodname_actions %} workflows.'
-layout: inline
 versions:
   fpt: '*'
   ghec: '*'

content/copilot/concepts/copilot-billing/understanding-and-managing-requests-in-copilot.md

@@ -85,7 +85,7 @@ Each model has a premium request multiplier, based on its complexity and resourc
 
 {% data variables.copilot.copilot_gpt_41 %} and {% data variables.copilot.copilot_gpt_4o %} are the included models, and do not consume any premium requests if you are on a **paid plan**.
 
-If you use **{% data variables.copilot.copilot_free_short %}**, you have access to a limited number of models, and each model will consume one premium request when used. For example, if you make a request using the {% data variables.copilot.copilot_o3_mini %} model, your interaction will consume **one premium request**, not 0.33 premium requests.
+If you use **{% data variables.copilot.copilot_free_short %}**, you have access to a limited number of models, and each model will consume one premium request when used. For example, if you make a request using the {% data variables.copilot.copilot_gemini_flash %} model, your interaction will consume **one premium request**, not 0.25 premium requests.
 
 {% rowheaders %}
 
@@ -101,7 +101,6 @@ If you use **{% data variables.copilot.copilot_free_short %}**, you have access
 | {% data variables.copilot.copilot_gemini_flash %}                       | 0.25                           | 1                     |
 | {% data variables.copilot.copilot_gemini_25_pro %}                      | 1                              | Not applicable        |
 | {% data variables.copilot.copilot_o3 %}                                 | 1                              | Not applicable        |
-| {% data variables.copilot.copilot_o3_mini %}                            | 0.33                           | 1                     |
 | {% data variables.copilot.copilot_o4_mini %}                            | 0.33                           | Not applicable        |
 
 {% endrowheaders %}

content/copilot/how-tos/custom-instructions/adding-repository-custom-instructions-for-github-copilot.md

@@ -220,6 +220,67 @@ Did you successfully add a custom instructions file to your repository?
 
 {% endnote %}
 
+## Writing effective repository custom instructions
+
+The instructions you add to the `.github/copilot-instructions.md` file should be short, self-contained statements that provide {% data variables.product.prodname_copilot_short %} with relevant information to help it work in this repository. Because the instructions are sent with every chat message, they should be broadly applicable to most requests you will make in the context of the repository.
+
+The exact structure you utilize for your instructions file will vary by project and need, but the following guidelines provide a good starting point:
+
+* Provide an overview of the project you're working on, including its purpose, goals, and any relevant background information.
+* Include the folder structure of the repository, including any important directories or files that are relevant to the project.
+* Specify the coding standards and conventions that should be followed, such as naming conventions, formatting rules, and best practices.
+* Include any specific tools, libraries, or frameworks that are used in the project, along with any relevant version numbers or configurations.
+
+The following instructions file is an example of these practices in action:
+
+```markdown
+# Project Overview
+
+This project is a web application that allows users to manage their tasks and to-do lists. It is built using React and Node.js, and uses MongoDB for data storage.
+
+## Folder Structure
+
+- `/src`: Contains the source code for the frontend.
+- `/server`: Contains the source code for the Node.js backend.
+- `/docs`: Contains documentation for the project, including API specifications and user guides.
+
+## Libraries and Frameworks
+
+- React and Tailwind CSS for the frontend.
+- Node.js and Express for the backend.
+- MongoDB for data storage.
+
+## Coding Standards
+
+- Use semicolons at the end of each statement.
+- Use single quotes for strings.
+- Use function based components in React.
+- Use arrow functions for callbacks.
+
+## UI guidelines
+
+- A toggle is provided to switch between light and dark mode.
+- Application should have a modern and clean design.
+```
+
+You should also consider the size and complexity of your repository. The following types of instructions may work for a small repository with only a few contributors, but for a large and diverse repository, **these may cause problems**:
+
+* Requests to refer to external resources when formulating a response
+* Instructions to answer in a particular style
+* Requests to always respond with a certain level of detail
+
+For example, the following instructions **may not have the intended results**:
+
+```markdown
+Always conform to the coding styles defined in styleguide.md in repo my-org/my-repo when generating code.
+
+Use @terminal when answering questions about Git.
+
+Answer all questions in the style of a friendly colleague, using informal language.
+
+Answer all questions in less than 1000 characters, and words of no more than 12 characters.
+```
+
 ## Repository custom instructions in use
 
 The instructions in the `.github/copilot-instructions.md` file are available for use by {% data variables.copilot.copilot_chat_short %} as soon as you save the file. The complete set of instructions will be automatically added to requests that you submit to {% data variables.product.prodname_copilot_short %} in the context of that repository. For example, they are added to the prompt you submit to {% data variables.copilot.copilot_chat_short %}.

content/copilot/reference/ai-models/choosing-the-right-ai-model-for-your-task.md

@@ -25,7 +25,6 @@ Use this table to find a suitable model quickly, see more detail in the sections
 | {% data variables.copilot.copilot_gpt_41 %} | General-purpose coding and writing | Fast, accurate code completions and explanations | Agent mode, visual |
 | {% data variables.copilot.copilot_gpt_4o %} | General-purpose coding and writing | Fast completions and visual input understanding | Agent mode, visual |
 | {% data variables.copilot.copilot_o3 %} | Deep reasoning and debugging | Multi-step problem solving and architecture-level code analysis | Reasoning |
-| {% data variables.copilot.copilot_o3_mini %} | Fast help with simple or repetitive tasks | Quick responses for code snippets, explanations, and prototyping | Lower latency |
 | {% data variables.copilot.copilot_o4_mini %} | Fast help with simple or repetitive tasks | Fast, reliable answers to lightweight coding questions | Lower latency |
 | {% data variables.copilot.copilot_claude_opus %} | Deep reasoning and debugging | Complex problem-solving challenges, sophisticated reasoning | Reasoning, vision |
 | {% data variables.copilot.copilot_claude_sonnet_35 %} | Fast help with simple or repetitive tasks | Quick responses for code, syntax, and documentation | Agent mode |
@@ -68,7 +67,6 @@ These models are optimized for speed and responsiveness. They’re ideal for qui
 | Model | Why it's a good fit |
 |-------|---------------------|
 | {% data variables.copilot.copilot_o4_mini %} | A quick and cost-effective model for repetitive or simple coding tasks. Offers clear, concise suggestions. |
-| {% data variables.copilot.copilot_o3_mini %} | Provides low-latency, accurate responses. Great for real-time suggestions and code walkthroughs. |
 | {% data variables.copilot.copilot_claude_sonnet_35 %} | Balances fast responses with quality output. Ideal for small tasks and lightweight code explanations. |
 | {% data variables.copilot.copilot_gemini_flash %} | Extremely low latency and multimodal support (where available). Great for fast, interactive feedback. |
 

content/copilot/reference/ai-models/supported-ai-models-in-copilot.md

@@ -37,7 +37,6 @@ This table lists the AI models available in {% data variables.product.prodname_c
 | {% data variables.copilot.copilot_gpt_41 %} | OpenAI | GA | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} |
 | {% data variables.copilot.copilot_gpt_4o %} | OpenAI | GA | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} |
 | {% data variables.copilot.copilot_o3 %} | OpenAI | {% data variables.release-phases.public_preview_caps %} | {% octicon "x" aria-label="Not included" %} | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} |
-| {% data variables.copilot.copilot_o3_mini %} | OpenAI | GA | {% octicon "x" aria-label="Not included" %} | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} |
 | {% data variables.copilot.copilot_o4_mini %} | OpenAI | {% data variables.release-phases.public_preview_caps %} | {% octicon "x" aria-label="Not included" %} | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} |
 | {% data variables.copilot.copilot_claude_opus %} | Anthropic | GA | {% octicon "x" aria-label="Not included" %} | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} |
 | {% data variables.copilot.copilot_claude_sonnet_35 %} | Anthropic | GA | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} | {% octicon "check" aria-label="Included" %} |
@@ -60,7 +59,6 @@ The following table shows which models are available in each client.
 | {% data variables.copilot.copilot_gpt_41 %}                   | {% octicon "check" aria-label="Included" %}           | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}              | {% octicon "check" aria-label="Included" %}       |  {% octicon "check" aria-label="Included" %}     |    {% octicon "check" aria-label="Included" %}       |
 | {% data variables.copilot.copilot_gpt_4o %}                    | {% octicon "check" aria-label="Included" %}          | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}              | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}      |   {% octicon "check" aria-label="Included" %}        |
 | {% data variables.copilot.copilot_o3 %}              | {% octicon "check" aria-label="Included" %}          | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}              | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}      |   {% octicon "check" aria-label="Included" %}        |
-| {% data variables.copilot.copilot_o3_mini %}                   | {% octicon "check" aria-label="Included" %}          | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}              | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}      |   {% octicon "check" aria-label="Included" %}        |
 | {% data variables.copilot.copilot_o4_mini %}         | {% octicon "check" aria-label="Included" %}          | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}              | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}      |   {% octicon "check" aria-label="Included" %}        |
 | {% data variables.copilot.copilot_claude_opus %}  | {% octicon "check" aria-label="Included" %}           | {% octicon "check" aria-label="Included" %}         | {% octicon "check" aria-label="Included" %}              | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}      | {% octicon "check" aria-label="Included" %}          |
 | {% data variables.copilot.copilot_claude_sonnet_35 %}         | {% octicon "check" aria-label="Included" %}          | {% octicon "check" aria-label="Included" %}       | {% octicon "check" aria-label="Included" %}              |  {% octicon "check" aria-label="Included" %}      | {% octicon "check" aria-label="Included" %}      |  {% octicon "check" aria-label="Included" %}         |
@@ -91,7 +89,6 @@ For more information about premium requests, see [AUTOTITLE](/copilot/managing-c
 | {% data variables.copilot.copilot_gpt_41 %} | 0 | 1 |
 | {% data variables.copilot.copilot_gpt_4o %} | 0 | 1 |
 | {% data variables.copilot.copilot_o3 %} | 1 | Not applicable |
-| {% data variables.copilot.copilot_o3_mini %} | 0.33 | 1 |
 | {% data variables.copilot.copilot_o4_mini %} | 0.33 | Not applicable |
 | {% data variables.copilot.copilot_claude_opus %} | 10 | Not applicable |
 | {% data variables.copilot.copilot_claude_sonnet_35 %} | 1 | 1 |

content/copilot/tutorials/comparing-ai-models-using-different-tasks.md

@@ -75,15 +75,15 @@ def grant_editor_access(user_id, doc_id):
 * {% data variables.copilot.copilot_gpt_4o %} can recognize the pattern and provide a clear, concise explanation.
 * The task doesn't require deep reasoning or complex logic.
 
-## {% data variables.copilot.copilot_o3_mini %}
+## {% data variables.copilot.copilot_o4_mini %}
 
-OpenAI {% data variables.copilot.copilot_o3_mini %} is a fast, cost-effective reasoning model designed to deliver coding performance while maintaining lower latency and resource usage. {% data variables.product.prodname_copilot_short %} is configured to use OpenAI's "medium" reasoning effort.
+OpenAI {% data variables.copilot.copilot_o4_mini %} is a fast, cost-efficient model designed for simple or repetitive coding tasks. It delivers reliable, concise answers with very low latency, making it ideal for real-time suggestions and lightweight development workflows. {% data variables.copilot.copilot_o4_mini %} is optimized for speed and responsiveness, so you can quickly iterate on small code changes or get instant feedback on straightforward prompts.
 
 ### Example scenario
 
-Consider a scenario where you are working on a software licensing system. You have a list of user records, each stored as a dictionary with fields like `name`, `active`, and `signup_date`. You want to find only the active users, sorted by their signup date, so that the newest users appear last.
+Suppose you are building a utility script and need to filter a list of user records to include only active users, sorted by their signup date. The task is simple and doesn’t require deep reasoning or multi-step logic.
 
-Below is list of users you are working with:
+Here’s a sample list of users:
 
 ```python
 users = [
@@ -111,10 +111,11 @@ active_users_sorted = sorted(active_users, key=lambda user: user["signup_date"])
 print(active_users_sorted)
 ```
 
-### Why o3-mini is a good fit
+### Why {% data variables.copilot.copilot_o4_mini %} is a good fit
 
-* The task involves simple filtering and sorting, which doesn’t require deep reasoning.
-* Its fast responses make it ideal for quick iteration during development.
+* The task is straightforward and benefits from fast, low-latency responses.
+* {% data variables.copilot.copilot_o4_mini %} is optimized for cost and speed, making it ideal for quick edits, prototyping, and utility code.
+* Use this model when you want reliable answers for simple coding questions without waiting for unnecessary depth.
 
 ## {% data variables.copilot.copilot_gemini_flash %}
 

content/graphql/overview/rate-limits-and-node-limits-for-the-graphql-api.md

@@ -286,4 +286,6 @@ If {% data variables.product.github %} takes more than 10 seconds to process an
 
 You can check the status of the GraphQL API at [githubstatus.com](https://www.githubstatus.com/) to determine whether the timeout is due to a problem with the API. You can also try to simplify your request or try your request later. For example, if you are requesting a large number of objects in a single request, you can try requesting fewer objects split over multiple queries.
 
+If a timeout occurs for any of your API requests, additional points will be deducted from your primary rate limit for the next hour to protect the speed and reliability of the API.
+
 {% endif %}