'local memory' 검색 결과

Set up, configure, update, and troubleshoot persistent memory for OpenClaw agents. The plugin stores conversations locally and supports automatic recall, task summaries, reusable skills derived from successful tasks, and a visual memory manager.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting up persistent memory for OpenClaw
• Updating or troubleshooting the memory plugin
• Choosing local or external memory search models

Use MemOS Local to find past conversations, preferences, and decisions, then retrieve original messages or task context. The skill also guides sharing memories and reusable procedures with local agents or a configured team.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find preferences and decisions from past conversations
• Read original messages and surrounding dialogue
• Share memories with local agents or a team

Move legacy NanoClaw memory and Claude auto-memory into a shared structure used across providers. The skill separates lasting facts from standing instructions, updates indexes, records each file's outcome, and verifies recall after approval.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Migrating memory after a shared-memory update
• Organizing legacy CLAUDE.md and Claude auto-memory
• Separating lasting facts from standing instructions

Set up and troubleshoot a local agentmemory server by checking MCP connections, authentication, ports, and environment settings. Understand which optional memory features require additional configuration, model downloads, or token usage before enabling them.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Set up a local agentmemory connection
• Diagnose MCP connection failures
• Review authentication and custom ports

Guides HTTP integration with the agentmemory server for saving and searching knowledge. It explains authentication, request conventions, and endpoint references, including how to connect systems that do not support MCP, the agent tool connection protocol.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Saving and searching knowledge over HTTP
• Connecting a host that does not support MCP
• Checking authentication and response conventions

Connect an AI agent client to Memory Proxy, which adds team memory, skills, and knowledge to model requests. The guided workflow checks existing settings, tests connectivity, and writes the appropriate client configuration.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Connect an AI agent to team memory
• Reuse an existing proxy configuration
• Test connectivity before writing settings

Review an agent’s saved memory alongside project and personal instructions. Receive proposed destinations for useful entries and a cleanup report covering duplicates, outdated facts, conflicts, and unclear items, with approval required before changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning saved memory into shared project instructions
• Separating personal instructions from project conventions
• Finding duplicate or outdated memory

Gives AI agents persistent project memory for architecture, implementation patterns, and decisions. Supports saving, searching, and retrieving knowledge, automatically syncing it with project documentation, and viewing memory usage through a dashboard.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Save architecture decisions for later reference
• Search saved implementation patterns by type or tag
• Retrieve a specific design record by key

Orchestrate the remote rules registry — the shared registry (often connected as a local folder or git repo) that the project's rules are published to and pulled from. Three modes, picked from the user's wording: create scaffolds a new local rules registry ("create a local rules registry", "init a rules registry"); update migrates/promotes local knowledge-base rules from .unikit/memory/ into the remote registry with automatic semver bumps ("migrate local rules to the remote registry", "promote my rules to the registry", "push local rules", "publish local rules", "update the rules registry"); sync pulls registry updates back into memory ("sync the rules registry", "pull registry updates"). Pass "--module <id>" to scope to one knowledge-base module. This skill ONLY orchestrates the CLI (`unikit-ai rules *`) — it never edits .unikit.json or .unikit/memory/ sources directly.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Find and run local AI models with llama.cpp. Choose GGUF model files and quantization levels that fit available memory, launch a command line session or local server, and test an OpenAI-compatible API on your computer.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find models to run on a local computer
• Choose quantization for available memory
• Launch and test a local OpenAI-compatible API

Help Claude interpret workplace shorthand by storing people, acronyms, project names, and preferences in local files. Keep frequent references in CLAUDE.md and detailed context in memory/, so requests can be understood using recorded workplace knowledge.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Recording internal acronyms and terminology
• Linking nicknames to people and roles
• Looking up project codenames and background

Help Claude interpret workplace shorthand by storing people, acronyms, project names, and preferences in local files. Keep frequent references in CLAUDE.md and detailed context in memory/, so requests can be understood using recorded workplace knowledge.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Recording internal acronyms and terminology
• Linking nicknames to people and roles
• Looking up project codenames and background

Review candidate learnings in Claude Code's native auto memory (`~/.claude/projects/<project>/memory/`, machine-local) and run them through a five-critic council in parallel: generality, staleness, redundancy, evidence, format. Majority vote (3+ of 5) promotes the entry to MEMORY.md. Use when user says "promote memory", "review my learnings", "what should graduate to MEMORY.md", "five-critic council", or as monthly memory maintenance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Find language models on Hugging Face Hub and run them locally with llama.cpp. The skill helps compare GGUF model files, choose compressed versions that fit available memory, and prepare commands for a local chat server or command-line session.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find a model that fits local RAM or GPU memory
• Compare available GGUF files and sizes
• Prepare a local chat server command

Inspect CPU, memory, disk, and accelerator information alongside container and scheduler limits. Produce a JSON snapshot with identifying details removed and conservative worker and memory estimates for planning local workloads, without running stress tests.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing worker counts before a large local job
• Checking CPU and memory limits inside a container
• Comparing resource snapshots before and after changes

Ask questions about your journal, Obsidian vault, or other text notes, and continue conversations that remember earlier chats. The companion uses cognee memory with local databases, reads your notes without changing them, and saves conversations for later reference.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Asking questions about journal entries
• Finding information in an Obsidian vault
• Continuing a conversation with earlier chats in memory

Run smoke tests, or basic operational checks, for Mastra projects locally or in staging and production. Verify Studio screens, agents, tools, workflows, traces, and memory, then report results, blockers, and skipped checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking a local Mastra project before release
• Testing Studio and server deployments in the cloud
• Running targeted checks for agents or traces

Use Memori Cloud from Claude Code to consult stored preferences, decisions, and project history before substantive work, then save the exchange afterward. Recall can span sessions and use filters for dates and information types.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check previous decisions before coding
• Recall preferences and project requirements
• Review progress after time away

Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when a project contains docs/memory/, or when the user asks to remember, retrieve, update, compact, forget, or audit project memory. MemoryCustodian manages local plain-text project memory with minimal context loading.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Save project context and task handoffs as local Markdown documents that Claude, Codex, and other agents can share. The skill guides searching prior knowledge, recording evidence and remaining work, and checking the shared memory vault for structural problems.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Handing work from Claude to Codex
• Saving project context for a later session
• Finding earlier decisions and supporting evidence

문서·대화·프로젝트 정보를 알맞은 저장 위치로 정리합니다. 로컬 파일, 지식 기반, GitHub 등을 아우르며 중복 확인, 동기화, 검색을 진행합니다.

• 문서와 대화를 지식 기반에 저장
• 중복된 메모 정리
• 여러 저장 위치의 지식 동기화

Guides agents in choosing Cherry Studio tools for research, document conversion, memory, notifications, and other tasks. It explains when to use app tools or local runtimes, with checks for availability, configuration, and approval.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choose the right Cherry Studio tool for a task
• Read or convert local Office and PDF files
• Set up scheduled tasks and notifications

Provides persistent project memory for AI agents through a local MCP server, a tool interface for agents. Stores and searches architecture decisions and implementation patterns, syncs with project documentation, and includes a dashboard for viewing memory usage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Save architecture decisions for later reference
• Search previously recorded implementation patterns
• Retrieve design notes by key