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Cursor 编辑器的产品迭代与生态动态——AI 编码工具竞争中最受关注的玩家之一。

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第 21–24 条 · 共 24 条
5月26日周二
  1. @vista868

    作者指出只安装 Skill 还不够,为更好触发和应用,需要把 Skill 写入 Agent.md,并给出安装更新 Waza 的提示词,要求以后各种开发设计优先使用这套 skill。转引内容显示 Waza 支持 Claude Code、Codex、Cursor 和 Pi 作为 agent 运行时,包含 8 个 skill,无框架、无遥测。

    引用Tw93 (@HiTw93)@HiTw93

    🥷 Engineering habits you already know, turned into skills AI agents can run. Waza absorbed a mass of real project lessons recently. Now just as sharp for Mac native apps, CLI tools, and Rust as it is for web. Supports Claude Code, Codex, Cursor, and Pi as agent runtimes. Reviews your CLI like a shipped product. Debugs "works in source tree, breaks after install." Sweeps sibling instances after every fix. Blocks "fixed" until runtime evidence is verified. 25 anti-patterns, destructive command safety, treats fetched content as untrusted data. 8 skills, no framework, no telemetry. Your superpower prompt collection can be uninstalled. Too heavy. github.com/tw93/Waza

    推荐理由:原文给出把 Skill 写入 Agent.md 的提示词写法,读者可据此改善技能触发与应用效果。

5月25日周一
  1. @kimmonismus65

    代号 TrapDoor 的供应链攻击同时针对 npm、PyPI 和 Crates.io,投递 34 个恶意包,目标是加密货币、AI 和安全开发者,用于窃取钱包、SSH 密钥和云凭证。

    引用Socket (@SocketSecurity)@SocketSecurity

    More analysis, package details, IOCs, and GitHub-related activity here, including attacker-hosted payload/config infrastructure and PRs attempting to add .cursorrules / CLAUDE.md files to popular AI and developer projects: socket.dev/blog/trapdoor-cry…

    推荐理由:该攻击把 CLAUDE.md 与 .cursorrules 配置文件当作新入口,让安全从业者了解 AI 编程助手被利用的攻击路径。

5月21日周四
  1. @kimmonismus69

    Cursor 发布 Composer 2.5,在 Artificial Analysis 编码智能体指数上得分 62,比上一代 Composer 2 提升 14 分,位列第三,仅次于 Claude Opus 4.7(max)的 66 分和 GPT-5.5(xhigh)的 65 分。标准版每任务成本 0.07 美元、Fast 版 0.44 美元,而上述两款更高分模型分别约为 4.10 和 4.82 美元。该模型仅在 Cursor IDE 和 Cursor CLI 提供,无外部 API,基于 Kimi K2.5 继续训练;推文作者认为性能略好却贵 60 倍已不再划算。

    引用Artificial Analysis (@ArtificialAnlys)@ArtificialAnlys

    Cursor's new Composer 2.5 takes third on the Artificial Analysis Coding Agent Index and is ~10-60x lower cost than the higher-effort Opus 4.7 and GPT-5.5 variants above it. This release puts Composer among the leading coding agent models, something that wasn’t clear for past releases @cursor_ai has released Composer 2.5, the latest model in its Composer line. Composer 2.5 scored 62 on our Coding Agent Index, a 14 point gain over Composer 2 (48). This puts it in third place of our tested agents, behind only Claude Opus 4.7 (max) in Claude Code (66) and GPT-5.5 (xhigh reasoning) in Codex (65). These cost $4.10 and $4.82 per task respectively, ~10x the cost of Composer 2.5 Fast ($0.44) and ~60x the cost of Composer 2.5 standard ($0.07). Key results for Composer 2.5 in Cursor CLI: ➤ Cost-quality Pareto frontier: At $0.07 (standard) and $0.44 (Fast) per task, Composer 2.5 is cheaper than every other agent scoring above 60 on the Index. Medium-effort peers cost $1.24–$2.21 per task; higher-effort variants land 3-4 points above at $4.10–$4.82 ➤ Per-benchmark gains vs Composer 2: +35 points on SWE-Bench-Pro-Hard-AA (12% → 47%), +2 points on Terminal-Bench v2 (64% → 66%), and +3 points on SWE-Atlas-QnA (69% → 72%). At 47%, Composer 2.5's score on SWE-Bench-Pro-Hard-AA is comparable to Claude Opus 4.7 (max) in Claude Code ➤ Among the fastest coding agents: Composer 2.5 Fast runs at an average wall time of 6.7 minutes per task, the third-fastest agent on the Artificial Analysis Coding Agent Index, behind only Claude Opus 4.7 (medium) in Claude Code (5.8m) and GPT-5.5 (medium) in Cursor CLI (6.2m) ➤ Fast mode enables better responsiveness at 6x pricing: Fast runs 30% faster than standard Composer 2.5, but is ~6x the cost per task ($0.44 vs $0.07). Token pricing is 6x higher for Fast: $3.00/$15.00 vs $0.50/$2.50 per million input/output tokens Model details: ➤ Base model: Continued training on @Kimi_Moonshot's open weights Kimi K2.5 as with Composer 2, with Cursor reporting ~85% of total compute from its own additional training and reinforcement learning ➤ Pricing: $0.50/$2.50 per million input/output tokens for the standard variant; $3.00/$15.00 for the Fast variant (the default in Cursor) ➤ Available exclusively in Cursor: both Cursor IDE and Cursor CLI, an externally accessible API is not available Congratulations @cursor_ai and @mntruell on the impressive release!

    推荐理由:推文用每任务成本对比 Composer 2.5 与两个更高分编码智能体,读者可据此权衡编码任务上的性能与花费。

5月16日周六
  1. Dwarkesh Patel66

    Eric Jang 讲解如何从零构建 AlphaGo

    Eric Jang 在 Dwarkesh Patel 的播客中讲解了如何从零构建 AlphaGo,涵盖蒙特卡洛树搜索、价值网络与策略网络以及自我对弈训练。他对比了 AlphaGo 的 MCTS 与 LLM 的 RL,指出后者需在超长轨迹中解决信用分配问题,而前者每步可给出更优动作作为训练目标。

    推荐理由:从零构建 AlphaGo 的完整讲解,梳理搜索、自我对弈与价值函数如何协同,并延伸到 LLM 的 RL 与自动化研究边界。