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概要と使いどころ
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stor
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Use when the user asks to "remember project context", review saved findings, initialize runtime memory, archive stale work, reconcile notes, or erase a subject; manages authorized HOT/WARM/COLD working memory across all disciplines while preserving registry event ownership and privacy controls. Not for changing canonical registry facts - route those through the owning registry. 项目记忆/跨会话
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Memory management and FreeRTOS context for the Megahub ESP32 project. Use when dealing with heap allocation, stack size, task creation, inter-task communication, semaphores, queues, or any ESP32 memory constraints.
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Riverbed Memory の suppression entry を活用するときの判断基準と CLI 操作を案内する。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector s...
日本語の概要は準備中です。原文の説明を表示しています。
Single-skill wrapper for the 4-layer recall (durable memory → semantic DB → PostgreSQL → daily notes). Use BEFORE saying "I don't have context". Triggers: "search memory", "what do we know about X", "deep recall", "I don't remember".
日本語の概要は準備中です。原文の説明を表示しています。
F Agent Memory: A Git-Native Persistent Memory Solution for AI Coding Agents and Project Knowledge Management OKF Agent Memory introduces a standardiz
日本語の概要は準備中です。原文の説明を表示しています。
Debug iOS apps and profile performance using LLDB, Memory Graph Debugger, and Instruments. Use when diagnosing crashes, memory leaks, retain cycles, main thread hangs, slow rendering, build failures, or when profiling CPU, memory, energy, and network usage.
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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.
日本語の概要は準備中です。原文の説明を表示しています。
Windows/Linux memory dump, hiberfil.sys analizi — volatility3 ile process, credential, env var çıkarma, DPAPI master key kurtarma ve pypykatz entegrasyonu.
日本語の概要は準備中です。原文の説明を表示しています。
Detects and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing traditional executable files to disk. Activates for requests involving fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.
日本語の概要は準備中です。原文の説明を表示しています。
Detects and analyzes process injection techniques used by malware including classic DLL injection, process hollowing, APC injection, thread hijacking, and reflective loading. Uses memory forensics, API monitoring, and behavioral analysis to identify injection artifacts. Activates for requests involving process injection detection, code injection analysis, hollowed process investigation, or in-memory threat detection.
日本語の概要は準備中です。原文の説明を表示しています。
Detects fileless malware and in-memory attacks that execute entirely in RAM without writing persistent files to disk, evading traditional antivirus. Use when building detections for PowerShell-based attacks, reflective DLL injection, WMI persistence, and registry-resident malware. Activates for requests involving fileless malware detection, in-memory attacks, PowerShell exploitation, or living-off-the-land techniques.
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Write reusable ChatCrystal task memories after substantive work completes. Use when implementation or debugging produced a durable fix, pitfall, pattern, or decision worth preserving, and when the environment can either persist it through `write_task_memory` or emit a structured memory candidate for later save.
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Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.
日本語の概要は準備中です。原文の説明を表示しています。
Design AI memory systems with context management. TRIGGERS - Use when user needs help with ai-memory-system related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Design memory systems for AI agents. TRIGGERS - Use when user needs help with ai-agent-memory related tasks.
日本語の概要は準備中です。原文の説明を表示しています。
Import a memory export from another AI assistant into Claude's memory — conversationally, additively, and with the content treated as data.
日本語の概要は準備中です。原文の説明を表示しています。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.
日本語の概要は準備中です。原文の説明を表示しています。
Capture durable project memory from work, debates, debugging discoveries, learned conventions, deferred options, and session outcomes. Load when the user says remember this, save this learning, record what happened, update project memory, or preserve context for future agents.
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Promote project-specific memories into strict, small global memory only when they are cross-project, stable, useful, safe, and worth the global context cost. Load when the user says make this global, remember across projects, save this globally, or promote this learning.
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Retrieve task-relevant project and global memory without loading everything. Load when the user asks what we decided, recall prior context, find memory about a feature, explain past rationale, resume a task, or check deferred ideas.
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Manage persistent memory for autonomous coding. Use when storing/retrieving knowledge, managing Graphiti integration, persisting learnings, or accessing episodic memory.
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Performance optimization guidelines for OneKey React/React Native applications. Use when optimizing app performance, fixing UI freezes/lag, reducing re-renders, handling concurrent operations, or analyzing performance bottlenecks. Triggers on performance, optimization, optimize, slow, lag, freeze, hang, jank, stutter, memory, leak, concurrent, batching, batch, memoization, memo, bridge, windowSize, contentVisibility, FlashList, re-render, fps, tti, bundle.
日本語の概要は準備中です。原文の説明を表示しています。