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Cursor can now show your agent's context usage as an interactive report in a canvas. The context explorer breaks down where tokens go across the system prompt, tool definitions, rules, skills, and more.

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Cursor

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37,814 просмотров • 3 месяцев назад •via X (Twitter)

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You can now see a breakdown of your agent's context usage in Cursor 3.3. Use these stats to diagnose context issues and improve your setup across rules, skills, MCPs, and subagents.
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MagicPath is now available as an official plugin for Cursor. Give Cursor an infinite canvas where you can view and edit interactive code, build apps that are instantly sharable. Use your local files, skills, etc. And with Composer 2.5 you can design at the speed of thought ⚡️
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MagicPath is now available as an official plugin for Cursor. Give Cursor an infinite canvas where you can view and edit interactive code, build apps that are instantly sharable. Use your local files, skills, etc. And with Composer 2.5 you can design at the speed of thought ⚡️

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I used the new Cursor agent + CopyCoder to build a Calendly frontend clone in 20mins Cursor agent now: - runs terminal commands - picks it's own context - executes more jobs with one prompt Crazy where this is going
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Using skills with lots of tool calls or research? In Visual Studio Code, you can now run skills in a dedicated sub agent so your main chat context stays clean and focused ⚡
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Codex and ChatGPT can now understand the context of your recent work. Opt into Computer History to give ChatGPT richer context, so it can pick up where you left off, understand patterns in your work, and suggest skills or scheduled tasks for work you repeat.
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update: the blackhole pivoted ⚫️ it started as a break reminder. then Jeryd asked "can it grow based on how many tokens I'm using?" and Romina Roman made the fair point that the $20 plan is already a built-in break reminder 😅 so now it's a context usage indicator for Claude Code: the more context you burn, the bigger it gets the blackhole reminds you to /compact 💀
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update: the blackhole pivoted ⚫️ it started as a break reminder. then Jeryd asked "can it grow based on how many tokens I'm using?" and Romina Roman made the fair point that the $20 plan is already a built-in break reminder 😅 so now it's a context usage indicator for Claude Code: the more context you burn, the bigger it gets the blackhole reminds you to /compact 💀

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American just got her home energy report for the year and the mailer says “Congratulations, your usage is 10% less” and breaks down the usage “We used less electricity and they charged us more” In America you can use less and they’ll still charge you more
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American just got her home energy report for the year and the mailer says “Congratulations, your usage is 10% less” and breaks down the usage “We used less electricity and they charged us more” In America you can use less and they’ll still charge you more

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Spatial now ships with a built-in MCP server, so you can use whole boards as context for Claude or Codex. As an example, you can let Claude analyze your visuals, reverse engineer a style prompt, and then save that prompt back as a new note.
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Spatial now ships with a built-in MCP server, so you can use whole boards as context for Claude or Codex. As an example, you can let Claude analyze your visuals, reverse engineer a style prompt, and then save that prompt back as a new note.

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The reality in enterprise AI = context > models Jaya Gupta & Arvind Jain dig into this topic and where AI breaks down in practice, who should own the context graph, and whether context graphs are really a trillion-dollar opportunity. Watch the full conversation linked below 👇
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in 9 minutes on the Tokyo stage, Angela Jang, head of product for the Claude platform, said the part most builders still haven't figured out: "a model is only as good as the context that you actually give it." that's the whole game now. not the prompt. the context. what your agent remembers. what skills it can pull. what it learns from its own past runs. anthropic now ships all three: memory, skills, and dreaming. agents that inspect their own trajectories and self-improve. demoed live this week. the prompt was never the bottleneck. the context was. most people are still tweaking words in a chat box. the ones who get this engineer the context their agents run on. watch the 9 minutes. then read the full breakdown below ⬇️
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in 9 minutes on the Tokyo stage, Angela Jang, head of product for the Claude platform, said the part most builders still haven't figured out: "a model is only as good as the context that you actually give it." that's the whole game now. not the prompt. the context. what your agent remembers. what skills it can pull. what it learns from its own past runs. anthropic now ships all three: memory, skills, and dreaming. agents that inspect their own trajectories and self-improve. demoed live this week. the prompt was never the bottleneck. the context was. most people are still tweaking words in a chat box. the ones who get this engineer the context their agents run on. watch the 9 minutes. then read the full breakdown below ⬇️

Avid

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I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:
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I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:

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is now the AI builder for everyone. The new v0 uses agentic AI to plan, research, build, and debug. It works in context, across multiple steps, and adapts as you go. If you have an idea, v0 can build it.
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