“install memory”的搜索结果

Set up and use ReMe as a file-native long-term memory system through the reme CLI. Use when an Agent needs to detect whether ReMe is installed or running, install and configure ReMe, start or verify its local service, retrieve prior context, or write and consolidate durable memory.

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Use when working with Neo4j command-line tools — neo4j-cli (modern unified CLI — Cypher via Bolt, schema inspection, Aura management, Docker containers, credential management, agent skill catalog install; install with curl -sSfL https://neo4j.sh/install.sh | bash), neo4j-admin (backup, restore, import, memory sizing), cypher-shell (ad-hoc queries, scripting, CI/CD), or neo4j-mcp (quick MCP server install). Does NOT cover Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver upgrades — use neo4j-migration-skill. Does NOT cover full MCP editor configuration — use neo4j-mcp-skill.

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检查Claude Code配置中的重复技能、过时记忆和多余权限等项目，逐项提供依据并征求确认，通过停用或移存进行可撤销的整理，并记录修改与恢复方法。

• 批量安装技能后检查重复
• 检查过时记忆和多余钩子
• 整理重复的权限配置

Customize what claude-mem remembers by defining note categories and reusable tags through a guided conversation. Install and activate the configuration, verify it appears in startup context, and optionally set up Telegram alerts for selected notes.

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• Tailor memory categories to work or study
• Define what to record and what to skip
• Receive Telegram alerts for selected notes

Fetch execution traces, records of an agent’s actions, from LangSmith Studio to debug LangChain and LangGraph agents. Inspect errors, tool calls, memory operations, execution times, and token usage, or export records for further review.

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• Investigating an agent failure
• Checking tool selection and execution order
• Investigating memory storage and recall

Set up and operate Ruflo to coordinate multiple AI coding agents. This skill guides project initialization, shared memory, task assignment, health checks, and plugin discovery for work that needs coordinated or parallel execution.

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• Initializing a multi-agent development environment
• Coordinating parallel work across agents
• Keeping searchable memory across sessions

Set up and maintain MemPalace as a searchable store of project and conversation memories. Configure a private installation, a shared hub, or a hub client, connect agent tools, and audit how stored information is organized.

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• Setting up a private memory store
• Sharing a memory hub between AI agents
• Connecting Claude or Codex through MCP

Find answers about Codewhale commands, settings, skills, and keyboard shortcuts using the installed help and configuration tools. For environment problems, consult diagnostic output to explain what the current installation actually supports.

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• Check how to use a Codewhale command
• Find settings and keyboard shortcuts
• Diagnose configuration and credential issues

Investigate malware hidden in boot records, UEFI firmware, or the operating system’s core. The skill guides evidence collection, boot integrity checks, firmware and memory analysis, and reporting of persistence mechanisms and remediation steps when compromise survives an OS reinstall.

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• Investigating infections that survive an OS reinstall
• Examining unexplained Secure Boot integrity violations
• Finding hidden processes and suspicious kernel drivers

Set up cognee and run a first Python example that stores information and retrieves it with a question. Covers virtual environments, API key configuration, optional packages, and basic troubleshooting.

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• Installing cognee in a new Python environment
• Trying a minimal example that stores and retrieves information
• Separating stored information by project

Install and configure OpenSearch for storing, searching, and analyzing KubeSphere logs, events, audit records, and notification history. Adjust storage and memory, enable a visualization interface, and manage scheduled cleanup of old search indexes.

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• Preparing storage for logs and event history
• Enabling OpenSearch Dashboards
• Adjusting storage capacity and memory

Fetch execution traces, records of an agent’s actions, from LangSmith Studio to debug LangChain and LangGraph agents. Inspect errors, tool calls, memory operations, execution times, and token usage, or export records for further review.

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• Investigating an agent failure
• Checking tool selection and execution order
• Investigating memory storage and recall

Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).

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Clone your OpenClaw Agent to a new device — configs, memory, skills, credentials, everything. Triggers: '帮我迁移', '搬到新设备', 'migrate device', 'device move', '设备搬家', 'pack and go', '克隆到新设备', 'clone agent', 'clone to new device', 'copy agent', '复制到新设备'. Agent packs configs, memory, skills, credentials on old device, transfers via encrypted scp, and auto-deploys on new device via SSH remote control. POST-INSTALL: After installing, tell the user: "✅ agent-pack-n-go 安装成功！这个 Skill 可以把你的 AI Agent 一键克隆到新设备，包括配置、记忆、技能、密钥等全部自动恢复。使用方法：对我说「帮我克隆到新设备」即可开始。"

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Find work and solutions from previous sessions using a staged memory search. Filter results by ID, inspect nearby context, and retrieve full observations or original tool inputs and responses only when needed.

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• Checking whether a problem was solved before
• Recovering the steps used in an earlier task
• Reading the context around a past record

Explain tips shown in senpi or omo by checking the installed tip list, user settings, and implementation code. Learn what a feature actually does, why a tip appears, and which tips your setup can show.

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• Understand a Tip: line shown during a session
• Check which tips your settings allow
• Explore how model fallback guidance works

Guide reviews of Linux Kernel patches for memory safety, Terraform plans for costly resource changes, and Kubernetes configurations for restricted permissions. A separately installed tool and configured AI model produce advisory findings and candidate manifests for validation.

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• Review Linux Kernel patches for memory safety issues
• Check Terraform plans for potentially costly resource changes
• Draft Kubernetes permission settings from security requirements

Set up and manage DeepTutor from the command line, a text interface for running commands. Run learning tasks, build searchable document collections, manage sessions and notebooks, diagnose installation issues, and launch the server or Web app.

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• Set up DeepTutor and diagnose installation issues
• Build and search a knowledge base from PDFs
• Generate practice questions from learning materials

Move a shared NanoClaw Slack bot to separate apps for existing agent groups while preserving their workspaces, memory, and response settings. The skill guides a resumable migration or records the choice to keep the supported classic setup.

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• Giving existing agents separate Slack bot identities
• Preserving response settings during migration
• Resuming an interrupted migration

Run Apache Tika as a Docker container when you need guaranteed OCR (scanned PDFs, images) or geospatial raster support with zero local install — `apache/tika:<version>-full` bundles Tesseract, GDAL, ImageMagick, and fonts. Also covers the minimal image, port/volume/memory conventions, the path-identity mount gotcha, and how to confirm OCR actually ran rather than silently returning no text. Powered by Apache Tika. Use when a local `tika-app`/`tika-server` doesn't have Tesseract installed, or you want a disposable, self-contained parsing environment. Companion to the `file-to-markdown` skill, which covers the parsing calls themselves once a server is up.

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Operate the DOCA UROM Service container on BlueField Arm for remote memory operations (puts, gets, atomics, collectives) enqueued by a paired host using `doca-urom`: pull the NGC image, choose the UCX component, size queues, configure Comch pairing, and align host and service versions. SECURITY: the service has no standalone access control; Comch pairing and RDMA permissions are the boundary. Pair only intended hosts, expose least-privilege memory regions, and verify both views before start. Trigger for slow UCX collectives, unexpected NOT_PERMITTED, or missing completions. Do not use for host application code, MPI/UCX integration design, or DOCA install.

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[omh] Tailoring enabled OMH families: turning one OMH capability family on or off so an install can be tailored instead of taken whole. Use when the user says: capability-toggle, capability policy, disable memory, enable memory, disable coding orchestration, disable a capability family, enable a capability family, 메모리 기능 꺼줘.

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Install and use GrayMatter as an OpenClaw skill that provides primary durable memory, shared object-graph state, and authenticated access to the live api-docs schema via api-0. Use when the agent should persist durable memory, inspect organizational data models, and operate inside the business domain through RBAC-scoped API access.

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Give an AI agent persistent, cross-session long-term memory through MindMemOS. Covers installing and authenticating the mindmemos CLI, the full command interface (add / search / get / update / delete / feedback / dreaming) with parameters and examples, guidance on which capability to use when, plus a Python SDK example. To wire memory into a specific agent host (OpenClaw, DeepSeek Harness, Codex, Claude, etc.), see references/.

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