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15:27

Anthropic's internal ELI5 skill: explain like I'm five, with HTML visuals

Anthropic 内部高频使用的 ELI5 命令：先画大图，再讲细节

Anthropic has been using an ELI5 Skill internally, triggered by /eli5 <topic>. It instructs the agent to explain a subject to a complete newcomer: avoid jargon, favor one big picture over dense text, and render complex ideas through an HTML artifact. The real payoff, as the post argues, is not simpler wording but forced knowledge restructuring — the agent must establish a mental model before diving into details and edge cases. Borrowed from Reddit's 'explain like I'm five' culture, this is a reusable output constraint for agent prompts, independent of any specific model, and easy to replicate in tools that support slash commands or custom skills. Useful for engineers tuning Claude or other agent output formats.

x.com · 1 min · Agents · AI Engineering · Prompt Engineering
06:00

A beautiful, modern & opinionated Linux distribution by DHH

一个由 DHH 出品的“有主见”的现代 Linux 发行版

Omarchy is a Linux desktop distribution led by DHH, designed to deliver a beautiful and coherent out-of-the-box experience. It bundles a curated set of software—terminal, Neovim, AI tooling, TUIs, GUIs, browsers, and more—alongside unified hotkeys, clipboard history, reminders, and system utilities. Instead of a neutral base, it encodes the author's opinions directly into defaults, reducing configuration burden while keeping a consistent workflow. The repository version-controls install scripts, dotfiles, themes, and an extensive manual mirrored to a docs site, making the entire setup reproducible and auditable. It also includes agent-related files (AGENTS.md, skills) for AI coding assistants. Ideal for developers and creators who want a polished, opinionated environment without assembling one from scratch.

github.com · 2 min · Agent Engineering · Developer Tools · Dotfiles · Linux · Neovim
06:00

Long-term memory for coding agents with cross-vendor handoffs

让编码 Agent 共享长期记忆，跨工具无缝交接工作流

ai-memory is a Rust-based long-term memory service for coding agents, addressing context loss when switching between tools like Claude Code, Codex, or Command Code. It uses MCP configuration and lifecycle hooks to automatically capture prompts, tool calls, and session boundaries, then compiles a concise summary and handoff at session end. The wiki is stored as plain Markdown in a git repo—grep-able, Obsidian-friendly, and backup-friendly—with no vector database to maintain. Retrieval blends FTS5, entity-match RRF, and graph-neighbor ranking, with optional embeddings and an optional LLM for consolidation. Best for engineers juggling multiple AI coding agents who want project memory to persist across sessions and vendors.

github.com · 62 min · Agent Engineering · Ai-Memory · CLI · Context Engineering · Mcp
06:00

Self-evolving context database for AI agents

为 AI Agent 设计的自演进上下文数据库

OpenViking is an open-source context database for AI agents. It unifies agent memory, knowledge resources, and skills into a single viking:// virtual file system, letting agents locate context with familiar file commands instead of querying an opaque vector store. Content is indexed into three tiers — L0 abstract, L1 overview, L2 details — at write time and loaded on demand, which cuts token usage and latency. Retrieval is directory-recursive: vector search first lands on the best-matching directory, then drills down layer by layer so results keep their surrounding context. Every query leaves an observable browsing trajectory that can be traced when answers go wrong. The project ships a CLI, server, benchmark harness, and integrations for Claude Code, Codex, Cursor, MCP clients, and more. It is well suited for engineers building agent memory, agentic RAG, or context engineering pipelines.

github.com · 19 min · Agent-Memory · Agentic RAG · Context Database · Context Engineering