Focused crawls are collections of frequently-updated webcrawl data from narrow (as opposed to broad or wide) web crawls, often focused on a single domain or subdomain.
Focused crawls are collections of frequently-updated webcrawl data from narrow (as opposed to broad or wide) web crawls, often focused on a single domain or subdomain.
TIMESTAMPS
The Wayback Machine - https://web.archive.org/web/20250426085553/https://github.blog/changelog/
You can now use the user prompt improvement feature in the GitHub Models playground. This new feature helps transform vague or broad prompts into clearer, more specific, and optimized ones for better model outputs. With just a few clicks, you can refine prompts to improve clarity, add focus, or adjust tone and style to match your needs. By providing specific suggestions—like requesting a particular format or style—you can save time and achieve high-quality, actionable results.
Try it out today and unlock more potential in your AI experimentation!
CodeQL is the static analysis engine behind GitHub code scanning, which finds and remediates security issues in your code. We’ve recently released version 2.21.1 of CodeQL. Here’s what’s new and improved in this release.
GitHub Actions
This CodeQL release coincides with the general availability of support for analyzing GitHub Actions workflows. Learn more in the dedicated changelog post.
We’ve improved alert fix suggestions for the actions/missing-workflow-permissions query, making it easier for you to resolve alerts.
JavaScript/TypeScript
We’ve added new detections of sources and sinks in Next.js and DOM element references, improving the detection of XSS issues.
We’ve enhanced path injection detection for several additional methods.
We’ve fixed an issue where tsconfig.json files containing array literals and trailing commas weren’t correctly extracted.
Ruby
We’ve improved the rb/useless-assignment-to-local query, so you’ll see fewer false positives and will get helpful documentation for alerts.
The rb/uninitialized-local-variable query now only generates an alert when a variable is used as a method call receiver. This should reduce noise. In addition, new help content is available for this query.
Calls to super without explicit arguments now have their implicit arguments generated, resulting in more accurate analysis.
For a full list of changes, check out the complete changelog for version 2.21.1. Every new version of CodeQL is automatically deployed to users of GitHub code scanning on github.com. The new functionality in CodeQL 2.21.1 will also be included in GitHub Enterprise Server (GHES) version 3.18. If you’re using an older version of GHES, you can manually upgrade your CodeQL version.
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Linking a pull request to an issue makes it easy for collaborators to see that work for the issue is underway. Today, when a linked pull request is merged, the associated issue is automatically closed.
But for many teams, merging a PR doesn’t mean the work is done. There might be QA, validation, or follow-up steps before an issue is truly resolved. With this new repository setting, you can choose whether merging a pull request should automatically close its linked issues.
Repository admins and maintainers can manage this setting under Repository settings → General → Issues. It’s enabled by default to preserve existing behavior.
For questions and feedback, join the discussion in GitHub Community.
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Copilot code review now covers over 90% of the file types typically found in pull requests, so more of your code benefits from intelligent insights.
We’ve also improved the quality of suggestions. Copilot code review now surfaces higher-quality, more actionable feedback by better handling of low-confidence and suppressed results. These improvements are especially noticeable in C#, where Copilot now provides more accurate and relevant suggestions with improved version awareness.
In addition, Copilot has improved its ability to understand context. Instead of primarily looking at the file diff in the pull request, it now considers the entire file. This leads to more holistic and relevant review suggestions.
For customers affected by ongoing grace periods, GitHub will automatically update the enable for new repositories security configuration setting for customers not opted out. This change helps you avoid unexpected billing charges without manual effort needed from your part.
Team and Enterprise customers with a configuration applied before April 1, 2025 enabling paid security features for newly created private repositories will see one of the following two changes applied:
Configurations with enable for new repositories set to for all public and private repositories will be adjusted to for all public repositories only.
Configurations with enable for new repositories set to for all private repositories will be adjusted to for no newly created repositories.
Customers who haven’t yet opted out with a representative from GitHub will see these settings enabled on the follow dates:
Team customers will see this change on April 23, 2025.
Enterprise customers will see this change on April 28, 2025.
GitHub code scanning now offers enhanced security protection for your GitHub Actions workflow files through CodeQL analysis, which is now generally available. This feature enables you to identify and remediate security vulnerabilities in your Actions workflows through automated code scanning, helping prevent potential security issues before they impact your CI/CD pipeline. CodeQL automatically analyzes your workflows to detect common security vulnerabilities, including missing required permissions, dangerous inputs without proper validation, and script injection vulnerabilities.
During the public preview period, we’ve helped secure over 158,000 repositories, detecting more than 800,000 potential vulnerabilities in Actions workflows, with approximately 15% of these issues being fixed by repository maintainers. This strong adoption demonstrates the value of automated security analysis for CI/CD workflows that use GitHub Actions.
For repositories using code scanning’s default setup, we will now automatically enable Actions workflow analysis when workflow files are detected in the default branch. For repositories using advanced setup, simply add the actions language to your existing configuration to enable this protection.
We’ve also added Copilot autofix functionality for the actions/missing-workflow-permissions query, one of the most frequent findings in Actions workflows. When this vulnerability is detected, you’ll receive automated fix suggestions to implement the principle of least privilege in your workflows, making remediation faster and easier.
To improve analysis quality, we’ve moved the actions/unversioned-immutable-action query to the extended query suite, allowing for more targeted and comprehensive analysis. If you’re using default setup, you can configure your scanning options to include extended queries. For repositories with advanced setup, you can specify this query suite in your CodeQL configuration. You can find more information about this change in the CodeQL release notes for 2.20.6.
Code scanning’s analysis of GitHub Actions workflow files will be available in GitHub Enterprise Server 3.18.
Dependabot users can now schedule custom update frequencies by using cron expressions in schedule.interval in the Dependabot configuration file. This enhances the predefined intervals (daily, weekly, and monthly) and provides a more generic and robust solution. This gives Dependabot users the ability to define custom schedules that meet their specific needs.
The new replication feed APIs are now live. While the legacy feeds will remain available—with limitations and scheduled brownout periods—until May 29, 2025, we strongly encourage all users to begin transitioning to the new APIs as soon as possible.
To access the updated feeds ahead of the deprecation, include the npm-replication-opt-in header with a value of true in your requests. This will route your traffic to the new APIs, bypassing the legacy feeds and avoiding any disruptions during brownout phases.
Please note that starting May 29, 2025, the legacy feeds will be fully deprecated. After this date, all requests to the replication feeds will automatically be served by the new APIs, regardless of header usage.
This change is part of our ongoing efforts to improve the performance and reliability of our services. We appreciate your understanding and cooperation during this transition.
Check out the migration guide and join the discussion in GitHub Community.
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During March and April, GitHub Mobile introduced several updates, including bug fixes, accessibility improvements, and a range of new features to make coding and collaboration on the go more seamless. From selecting the model you prefer when using Copilot, to a new way to search within a file, these updates enhance productivity and keep you connected wherever you are.
The GitHub Copilot for Xcode extension now allows you to ask questions about your entire codebase using the @workspace context. Additionally, we have added support for new models, including Claude 3.7 Sonnet and GPT 4.5, to enhance your chat conversations and introduce some UX improvements to boost your productivity.
What’s new ✨
@workspace context: By referencing @workspace in Copilot Chat, you can ask questions about your entire codebase. GitHub Copilot will analyze your project’s codebase and provide detailed answers, including references to relevant files and symbols. The @workspace context helps you find the code you’re looking for, understand how functionality is implemented, and much more.
New model options: Claude 3.7 Sonnet and GPT 4.5 are now available in the model selector of Copilot Chat. Learn more about the models available in our documentation.
UX improvements & bug fixes ⚡️
This update also includes a few other UX improvements and bug fixes:
Simplified Workflow: Open Copilot Chat with a single click from our Copilot for Xcode app, making it easier and faster to access. This helps streamline the development process and reduce time spent navigating various menus.
Bug fixes: Notifications for enabling background functionality to address crashes or non-responsive states.
With delegated alert dismissal for secret scaning alerts, you can require a review process before alerts are dismissed. This helps you better manage your security risk as well as meet audit and compliance requirements.
Managing alert dismissal requests is now available with the REST API, offering flexibility for triage and reviews by integrating with your existing workflows.
Reviewers can retrieve dismissal requests for an organization or repository with the following endpoints:
As part of our effort to help optimize activity feed load times and reduce timeouts, we’re migrating the organizational feed to a newer infrastructure. This migration from our existing system to an improved infrastructure will enable us to have a more performant experience for all users interacting with the organizational feed.
While this change is primarily back end, with minimal impact to the user experience, organizational feed users may notice a slight change to the UI. In our current experience, push event activity notifications have one line per event, mixed in with other event types in the feed. With this improvement, users can see all push events grouped into one card, sorted in chronological order with the most recent events appearing first.
When is the change occurring?
This change will occur on April 21st, 2025 for all users that interact with the organizational feed.
Copilot Chat on github.com now supports organization custom instructions! This feature allows Copilot Enterprise customers to set default instructions for all users in their organization, ensuring a consistent experience across teams.
Getting started
Navigate to your organization settings on github.com.
Select the Copilot tab.
Click Custom Instructions in the left sidebar.
Add your custom instructions in the provided text box.
That’s it! Copilot will now apply custom instructions to all chats by members of your organization.
Looking for inspiration? 💡
Here are some suggestions to get you started.
Set consistent standards: For questions related to security, always redirect to #ask-security on Slack.
Establish information architecture: Always refer to the Primer Knowledge Base when answering questions about frontend theming and components.
Steer response style: Never include code blocks in responses.
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MAI-DS-R1 is an updated version of DeepSeek-R1, refined by Microsoft AI. It handles complex queries more effectively, works across multiple languages, and provides access to previously restricted information. The model maintains the reasoning strengths of the original while improving reliability.
Sharing a Copilot Chat used to mean screenshots and copy-paste. Now it’s as easy as sending a link. Shared conversations are now available in public preview in immersive chat on github.com.
Sharing Copilot Chats makes it easier to:
🕵 Troubleshoot with teammates—like this chat digging into a React onClick issue.
🧠 Showcase learning workflows with a friend. Here’s an example walking through Python interview prep, step by step.
🤗 Drop useful insights into a pull request review or team chat—like this example that clears up an open team debate.
🎬️ Demo cool Copilot tricks on social—like this one where Copilot asks smart follow-up questions before jumping in.
How sharing works
Start a conversation. Once you enter your first prompt, the Share button will appear.
Click Share and copy the generated link. Anyone with the link can view the conversation.
If the chat includes private repository content or other restricted GitHub data, viewers will need the appropriate permissions to see it.
As the conversation continues, recipients will see new messages appear in real time.
You can unshare a conversation at any time to revoke access.
Shared conversations are currently in public preview for individual users (not members of organizations or enterprises). We’re actively working on expanding access to all Copilot users soon.
Codespaces will be undergoing global maintenance from 16:30 UTC on Monday, April 21 to 16:30 UTC on Tuesday, April 22. Maintenance will begin in our Europe, Asia, and Australia regions. Once it is complete, maintenance will start in our US regions. Each batch of regions will take approximately three to four hours to complete.
During this time period, users may experience intermittent connectivity issues when creating new Codespaces or accessing existing ones.
To avoid disruptions, ensure that any uncommitted changes are committed and pushed before the maintenance starts. Codespaces with uncommitted changes will remain accessible as usual after the maintenance is complete.
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Introducing AI-powered commit message generation with Copilot—available in the latest GitHub Desktop Beta. With a click of a new button in the commit message box, get your changes to upstream with speed, confidence, and an AI-crafted summary.
Copilot commit message generation is available to Copilot Free and all paid Copilot subscribers. Organizations and enterprises can enable it through the “Copilot in GitHub Desktop” policy.
Try it out today—download the GitHub Desktop v3.4.19-beta3 and see how Copilot can supercharge your commit process. Tell us what you think in the GitHub Desktop open source repo.
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The latest AI models from Cohere, Command A and Embed 4, are now available on GitHub Models.
Command A is a multilingual model designed for business-critical applications like retrieval-augmented generation (RAG) and agentic tasks. It excels at supporting knowledge assistants, improving demand forecasting, and optimizing eCommerce search.
Embed 4 is a multilingual model that transforms text, images, and mixed formats into unified vector representations. It is well-suited for processing high-resolution images and extracting key details from files like PDFs, slides, and tables.
Try, compare, and implement Command A in your code for free in the playground. Both Command A and Embed 4 are also available through the GitHub API for seamless integration into your applications.
Mistral Large is now deprecated in GitHub Models. Please transition to Mistral Large 24.11 to continue using the improved version with enhanced features.
OpenAI’s latest reasoning models, o3 and o4-mini, are now available in GitHub Copilot and GitHub Models bringing next-generation problem-solving, structured reasoning, and coding intelligence directly into your development workflow.
These models represent a major leap forward in capability and efficiency:
o3 is the most capable reasoning model in the o-series, ideal for deep coding workflows and complex technical problem solving.
o4-mini is the most efficient model in the series, combining low latency with high-quality output, full tools support, and multimodal inputs.
Both models are optimized for real-world development and support advanced features like function calling, structured outputs, and long-context handling (up to 200K tokens). Whether you’re building agentic tools, analyzing contracts, writing algorithms, or debugging across multiple layers, these models are designed to help you move faster with more accuracy and insight.
Availability in GitHub Copilot
o4-mini is now rolling out across all GitHub Copilot plans and o3 is available to Enterprise and Pro+ plans. You can access them through the model picker in Visual Studio Code and in GitHub Copilot Chat on github.com. To accelerate your workflow, whether you’re debugging, refactoring, modernizing, testing, or just getting started, select “o3” or “o4-mini” to begin using a new model. Stay tuned for updates on additional availability.
Enabling access
Copilot Enterprise administrators will need to enable access to these models through a new policy in Copilot settings. As an administrator, you can verify availability by checking your individual Copilot settings and confirming that policy is set to enabled for the specific model. Once enabled, you’ll see the model in the Copilot Chat model selector in VS Code and on github.com.
Both o3 and o4-mini will also be available through GitHub Models, enabling developers to experiment, build, and deploy AI-powered features faster than ever. In the GitHub Models playground, you can experiment with sample prompts, refine your ideas, and iterate as you build. You can also try them alongside other models, including those from Cohere, DeepSeek, Meta, and Microsoft.