653 个 · 按相关度排序
Rebuild the DSH node's persistent knowledge state. Runs register-claude.py to (re)create the dome.db schema and upsert agents/skills/tools/stack rows, then runs ingest.py to re-index kb/, logs/, docs, and agent core source into ChromaDB's dome-kb collection, then runs pre-spore-verify.py to confirm all 7 skill modules load and the akashic write+query roundtrip works. Idempotent — safe to run any time.
中文简介正在准备中。当前显示原文说明。
Ralph - persistent self-referential execution loop wrapping ultrawork with independent verifier verification
中文简介正在准备中。当前显示原文说明。
One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.
中文简介正在准备中。当前显示原文说明。
Read this skill before the first step that uses the built-in browser, the browser pane inside the Claude desktop app (also called the in-app browser, the browser pane, Claude's browser, or "your own browser"), whose tools are named mcp__Claude_Browser__* when the session runs in the desktop app and mcp__remote-devices__Claude_Browser__* when a cloud session is linked to the person's computer; before those tools are turned on there may be a single enable__mcp__remote-devices__Claude_Browser tool instead. It covers the pane's persistent sign-ins, tabs and preview_start, reading pages as text, site approvals, what the pane cannot open, and what to do when it cannot be reached. It is not for Claude in Chrome (mcp__claude-in-chrome__* tools), which has its own skill, and it does not decide which browser to use.
中文简介正在准备中。当前显示原文说明。
Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.
中文简介正在准备中。当前显示原文说明。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
中文简介正在准备中。当前显示原文说明。
Manage docs/steering/ as persistent project knowledge
中文简介正在准备中。当前显示原文说明。
Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.
中文简介正在准备中。当前显示原文说明。
Search claude-mem's persistent cross-session memory database. Use when user asks "did we already solve this?", "how did we do X last time?", or needs work from previous sessions.
中文简介正在准备中。当前显示原文说明。
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
中文简介正在准备中。当前显示原文说明。
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
中文简介正在准备中。当前显示原文说明。
Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static/dynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive applications.
中文简介正在准备中。当前显示原文说明。
Segundo cérebro persistente em Markdown — LLM Wiki no padrão Karpathy mantida como bundle Open Knowledge Format v0.2, com fontes imutáveis em raw/ e conceitos citados em wiki/. Use quando o usuário disser "segundo cérebro", "second brain", "adiciona isso ao meu brain", "salva na minha wiki", "ingere esse artigo/PDF/link", "o que minha wiki diz sobre", "o que meu brain sabe sobre", "consulta meu conhecimento", "lint da wiki", ou pedir para acumular conhecimento de fontes de forma durável. NÃO use para notas do Obsidian (pwdev-obsidian), planejamento de features (pwdev-feat) nem PRDs (pwdev-prd).
中文简介正在准备中。当前显示原文说明。
Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware with per-person contributions, praise, and growth areas. Use when asked for weekly retro, what shipped this week, or engineering retrospective.
中文简介正在准备中。当前显示原文说明。
Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics with persistent history and trend tracking. Team-aware: breaks down per-person contributions with praise and growth areas. Use when asked to "weekly retro", "what did we ship", or "engineering retrospective". Proactively suggest at the end of a work week or sprint. (gstack)
中文简介正在准备中。当前显示原文说明。
Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Use persistent mode only when user says "caveman mode", "talk like caveman", "use caveman", or invokes /caveman.
中文简介正在准备中。当前显示原文说明。
Explain Ponytail's intended tradeoffs and measurement boundary. It does not estimate code, cost, or speed savings for the current repository. One-shot display, not a persistent mode. Trigger: ponytail-gain, "ponytail gain", "what does ponytail save", "show ponytail impact", or "ponytail scoreboard".
中文简介正在准备中。当前显示原文说明。
Quick-reference card for all ponytail modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /ponytail-help, "ponytail help", "what ponytail commands", "how do I use ponytail".
中文简介正在准备中。当前显示原文说明。
Show ponytail's measured impact as a compact scoreboard: less code, less cost, more speed, from the benchmark medians. One-shot display, not a persistent mode, and not a per-repo number. Trigger: /ponytail-gain, "ponytail gain", "what does ponytail save", "show ponytail impact", "ponytail scoreboard".
中文简介正在准备中。当前显示原文说明。
Build, update, and query a persistent project knowledge graph from skills, memory, docs, and code structure — stdlib Python only, no external tools. Dual-mode: skill-library (agent-loom) or application (any consumer repo). Load when the user asks for a knowledge graph, project map, skill relationships, query the graph, update the graph, or trace how components connect. Auto-runs on memory-handoff and project-setup bootstrap. Also triggers on "build the graph", "what connects to X", "map this project".
中文简介正在准备中。当前显示原文说明。
Orchestrate persistent agent memory across coding sessions, repos, and tools. Load when the user asks to remember, recall context, save project memory, create a handoff, manage global memory, update memory, compact memory, audit memory, forget memory, continue from prior sessions, or before commit/push/git operations that checkpoint project state.
中文简介正在准备中。当前显示原文说明。
A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
中文简介正在准备中。当前显示原文说明。
Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.
中文简介正在准备中。当前显示原文说明。
Safety-case design for always-on agents with episodic memory. Covers data hygiene, privacy and security risk surfaces, cost controls, scope, user dependency concerns, retention, incident containment, and responsible deployment evidence. It identifies hazards and asks for named controls, tests, owners, and residual uncertainty; it does not provide legal, clinical, youth-safety, or jurisdictional determinations. Activate on: "agent safety", "always-on agent privacy", "agent cost control", "persistent agent risks", "AI companion safety", "agent data hygiene", "runaway agent costs", "parasocial AI risk", "/always-on-agent-safety". NOT for: architecture design (use always-on-agent-architecture), input design (use always-on-agent-inputs), application brainstorming (use always-on-agent-applications), healthcare compliance specifically (use hipaa-compliance).
中文简介正在准备中。当前显示原文说明。