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#Anthropic

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10/16Thu
  1. Jesse Vincent78

    Anthropic launches its official Skills system across Claude Code, Claude.ai, and the Claude API

    Anthropic rolled out its first-party Skills system simultaneously on Claude Code, Claude.ai, and the Claude API, and author Jesse Vincent quickly followed with a new version of Superpowers built on the official Skills.

    Why it matters: Drawing on nearly a month of hands-on use, the author compares the official Skills with his own setup and lays out the trade-offs involved in migrating.

10/13Mon
  1. Jesse Vincent37

    让 AI 写出好文风的一个怪招:先让 Claude 读《The Elements of Style》

    开发者 Jesse Vincent 发现,让 Claude 先读 Strunk 1920 年版《The Elements of Style》再写 README,成稿比原来短约 30%,文风也更合他意。他把该书 HTML 转成约 12,000 词的 Markdown,因 Anthropic 的版权过滤机制拒绝处理这本已进入公有领域的书,最终改用 GPT-5 Codex 完成删减。

    Awaiting translation

10/12Sun
10/9Thu
  1. Jesse Vincent78

    Superpowers: How the Author Used a Coding Agent in October 2025

    Author Jesse Vincent released Superpowers, a set of Skills built on Claude Code's new plugin system. Once installed, it injects a guiding prompt through the session-start hook, prompting Claude to proactively search for and use these Skills.

    Why it matters: The author packaged his own coding-agent workflow into an installable Skill plugin, so readers can directly reuse his implementation flow from brainstorming to TDD.

10/5Sun
  1. Jesse Vincent71

    How I Used a Coding Agent in September 2025: A Dual-Session Workflow with Claude Code

    The author walks through their full workflow with Claude Code: first isolating tasks with git worktree, then using a brainstorming prompt to make Claude ask only one question at a time and confirm the design in stages, and finally using a planning prompt to break the plan into small tasks and write them into docs/plans/.

    Why it matters: The author splits Claude Code into two sessions—an architect and an implementer—and shares reusable prompts plus a git worktree approach for isolating tasks.

10/2Thu
10/1Wed
  1. Hacker News · Context Engineering 讨论76

    Anthropic on Effective Context Engineering for AI Agents

    Anthropic's applied AI team argues that context engineering is a continuation of prompt engineering, and the core idea is picking the smallest set of high-signal tokens within a limited attention budget.

    Why it matters: Anthropic lays out a systematic approach to context engineering, covering the trade-offs among three long-task strategies: compression, note-taking, and sub-agents.

9/29Mon
  1. Jesse Vincent66

    Rewriting CLAUDE.md Rules with GraphViz's Dot Language

    The author rewrote a long block of CLAUDE.md rules as a GraphViz dot flowchart, using quoted strings as node names, different shapes to distinguish decisions, commands, and warnings, and giving each flow an explicit trigger condition.

    Why it matters: After rewriting the CLAUDE.md rules as a GraphViz dot flowchart, Claude followed the rules better, and this approach can be carried over to your own projects.

8/26Tue
7/13Sun
7/1Tue
  1. Hacker News · Context Engineering 讨论78

    Context Engineering for Agents: Four Strategies—Write, Select, Compress, and Isolate

    In his article, Lance Martin groups context engineering for agents into four strategies: writing (using scratchpads and memory to store information outside the context window) and selecting (pulling in memory, tool descriptions, and knowledge on demand).

    Why it matters: The article groups agent context management into four strategies—writing, selecting, compressing, and isolating—and shows how various products put them into practice, making it easy to compare against your existing workflow.

6/26Thu
6/24Tue
5/28Wed
5/23Fri
  1. Terminal-Bench · News32

    Anthropic 在 Claude 4 模型卡中引入 Terminal-Bench,Claude 4 Opus 创下 43.2% 新 SOTA

    Anthropic 将 Terminal-Bench 列为 Claude 4 模型卡七项基准之一,Claude 4 Opus 在 Terminal-Bench-Core 上取得 43.2% 的 SOTA 成绩。Dario Amodei 在 Code with Claude 主题演讲中也提及该基准。Terminal-Bench 团队表示将在未来几天验证 Claude 4 的表现并更新官方排行榜。

    Awaiting translation

5/14Wed
  1. Martin Fowler · Exploring Generative AI62

    用 LLM 构建 PlantUML 分步播放扩展 PlantUMLSteps

    作者用 LLM 构建了 PlantUMLSteps,为 PlantUML 时序图增加按步骤播放功能,把单张复杂图拆成登录、认证、仪表盘等逐步展示的步骤。开发中 Claude 在 Cursor Agent 模式下生成 StepParser 解析逻辑、Gradle 任务和 HTML 查看器,解析器最初在 newPage 属性、首个步骤标记前的声明处理上出错,经测试反馈修正后通过。

    Awaiting translation

5/8Thu
4/6Sun
3/18Tue