This release introduces the ability to hand off plans from the CLI to the cloud, in-line rendering of ASCII diagrams, and many quality-of-life improvements.

#Plan mode improvements in CLI

When a plan is generated, the CLI now shows a persistent decision menu. You can choose to build in the cloud or build locally to execute the plan.

Typing /plan takes you back to your current plan and its action menu. We've also added keyboard shortcuts in the prompt bar so you can use arrow keys to navigate options, Enter to execute the selected option, and Shift+Enter as a shortcut for "Build in cloud."

#Mermaid ASCII diagrams in CLI

Mermaid code blocks now render inline as ASCII diagrams in your CLI conversation. Flowcharts, sequence diagrams, state machines, class diagrams, and ER diagrams can all be displayed directly in the terminal.

Ctrl+O allows you to switch between the rendered diagram and the original mermaid source to see both representations.

#Other improvements

We've also made lots of improvements to the CLI focused on tooling, quality of life, and reliability.

This release introduces plugins for extending Cursor, improvements to core agent capabilities like subagents, and fine-grained network controls for sandboxed commands.

#Plugins on the Cursor Marketplace

Plugins package skills, subagents, MCP servers, hooks, and rules, into a single install. The Cursor Marketplace lets you discover and install plugins to extend Cursor with pre-built capabilities.

Our initial partners include Amplitude, AWS, Figma, Linear, Stripe, and more. These plugins cover workflows across design, databases, payments, analytics, and deployment.

Browse plugins at cursor.com/marketplace or install directly in the editor with /add-plugin.

Read more in our announcement.

#Sandbox network access controls

The sandbox now supports granular network access controls, as well as controls for access to directories and files on your local filesystem. Define exactly which domains the agent is allowed to reach while running sandboxed commands:

• User config only: restricted to domains in your sandbox.json
• User config with defaults: restricted to your allowlist plus Cursor's built-in defaults
• Allow all: unrestricted network access within the sandbox

Admins on the Enterprise plan can enforce network allowlists and denylists from the admin dashboard, ensuring organization-wide egress policies apply to all agent sandbox sessions.

#Async subagents

Previously, all subagents ran synchronously, blocking the parent agent until they complete. Subagents can now run asynchronously, allowing the parent to continue working while subagents run in the background.

Subagents can also spawn their own subagents, creating a tree of coordinated work. This allows Cursor to take on bigger tasks like multi-file features, large refactors, and challenging bugs.

We've also made some performance improvements to subagents since our last release. They now run with lower latency, better streaming feedback, and more responsive parallel execution.

Cursor can now work autonomously over longer horizons to complete larger, more complex tasks. Long-running agents plan first and finish more difficult work without human intervention.

In research preview and internal testing, long-running agents completed work that was previously too hard for regular agents. This led to larger, more complete PRs with fewer obvious follow-ups.

Cursor's long-running agent is now available at cursor.com/agents for Ultra, Teams, and Enterprise plans.

Read more in our announcement.

Agents are solving increasingly complex, long-running tasks across your codebase. This release introduces new agent harness improvements for better context management, as well as many quality-of-life fixes in the editor and CLI.

#Subagents

Subagents are independent agents specialized to handle discrete parts of a parent agent's task. They run in parallel, use their own context, and can be configured with custom prompts, tool access, and models.

The result is faster overall execution, more focused context in your main conversation, and specialized expertise for each subtask.

Cursor includes default subagents for researching your codebase, running terminal commands, and executing parallel work streams. These will automatically start improving the quality of your agent conversations in the editor and the Cursor CLI.

Optionally, you can define custom subagents. Learn more in our docs.

#Skills

Cursor now supports Agent Skills in the editor and CLI. Agents can discover and apply skills when domain-specific knowledge and workflows are relevant. You can also invoke a skill using the slash command menu.

Define skills in SKILL.md files, which can include custom commands, scripts, and instructions for specializing the agent’s capabilities based on the task at hand.

Compared to always-on, declarative rules, skills are better for dynamic context discovery and procedural “how-to” instructions. This gives agents more flexibility while keeping context focused.

#Image generation

Generate images directly from Cursor's agent. Describe the image in text or upload a reference to guide the underlying image generation model (Google Nano Banana Pro).

Images are returned as an inline preview and saved to your project's assets/ folder by default. This is useful for creating UI mockups, product assets, and visualizing architecture diagrams.

#Cursor Blame

On the Enterprise plan, Cursor Blame extends traditional git blame with AI attribution, so you can see exactly what was AI-generated versus human-written.

When reviewing or revisiting code, each line links to a summary of the conversation that produced it, giving you the context and reasoning behind the change.

Cursor Blame distinguishes between code from Tab completions, agent runs (broken down by model), and human edits. It also lets you track AI usage patterns across your team's codebase.

#Clarification questions from the agent

The interactive Q&A tool used by agents in Plan and Debug mode now lets agents ask clarifying questions in any conversation.

While waiting for your response, the agent can continue reading files, making edits, or running commands, then incorporate your answer as soon as it arrives.

You can also build custom subagents and skills that use this tool by instructing them to "use the ask question tool."