'memory' 검색 결과

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.

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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.

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Check a Bot’s connection to Hindsight and set up dedicated and shared memory stores. The skill also creates a user knowledge summary when needed and reports which other memory stores are available to read.

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• Setting up Hindsight for a Bot’s first use
• Checking the connection after a memory tool fails
• Separating project memories from shared knowledge

Investigate security incidents using memory dumps, saved copies of RAM. The skill guides memory acquisition, process and network analysis, suspicious code detection, and evidence extraction with Volatility and related tools, including checks for capture integrity.

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• Capturing RAM before shutting down a system under investigation
• Finding suspicious processes and network connections in memory
• Extracting executables and strings for malware analysis

Diagnose missing recall, failed captures, and connection errors in the OpenViking memory plugin for Codex. Check installation, configuration, authentication, and server readiness, then use the findings to guide fixes and verify that memory works again.

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• Investigate missing recall or unsaved conversations
• Check plugin status after installation or updates
• Diagnose 401 and 403 authentication errors

Calculate how to divide serving memory between recurrent state and KV cache, two memory pools used by hybrid models. Use startup logs and workload settings to recommend a ratio, estimate concurrency, and identify the limiting pool.

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• Choosing a memory ratio for a hybrid model
• Investigating limits on concurrent requests
• Recalculating memory allocation for context length

Acquire Linux memory with LiME and examine it using Volatility 3. Extract processes, network connections, command history, loaded kernel modules, and signs of injected code to support investigations of compromised Linux systems.

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• Acquiring memory from a compromised Linux system
• Comparing process lists to investigate hidden processes
• Reviewing command history and network connections

Analyze memory dumps with Volatility3 to find heap spraying, an attack that fills memory with attacker-controlled data. Examine suspicious allocations and repeated byte patterns, extract suspicious code, and report affected processes and memory regions in JSON.

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• Investigating suspected heap spraying in a memory dump
• Extracting suspicious code from memory
• Organizing evidence for detection rule development

Reduce GPU memory use by loading language models in 8-bit or 4-bit formats with bitsandbytes and HuggingFace Transformers. Includes configuration examples, QLoRA fine-tuning of compressed models, and optimizers that reduce memory needed during training.

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• Load larger models within limited GPU memory
• Compare 8-bit and 4-bit model settings
• Fine-tune a model with QLoRA

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.

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

Understand how agentmemory automatically records tool activity, prompts, and session boundaries through hooks, actions triggered by session events. Use it to check integration setup, investigate missing records, and distinguish capture from optional summaries and context injection.

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• Understanding automatic session recording
• Investigating missing observations
• Checking capture and summary settings

Guide an agent through searching past decisions before work, saving new decisions with their reasons, and treating corrections as lessons. The workflow helps distinguish useful long-term knowledge from temporary details, code facts, and routine activity already captured by hooks.

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• Checking earlier decisions before starting a task
• Saving a resolved issue with its underlying reason
• Preserving lessons from corrections

Investigate growing memory usage in Qwen Code CLI by comparing heap snapshots, records of objects in memory. Trace what keeps objects alive, identify likely causes, and repeat the workload to verify a fix.

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• Investigating steadily growing memory usage
• Tracing references that keep objects alive
• Finding growing arrays, caches, or event listeners

Turn recurring lessons in Claude's automatic memory into concise project rules. Choose a project-wide, file-specific, or personal rule location, include concrete commands, and clean up the original memory entry after confirmation.

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• Make repeated corrections into lasting rules
• Record the project's package manager
• Apply API rules to selected file paths

Design persistent agent memory that retains knowledge across sessions and retrieves relevant facts when needed. Compare storage approaches, track people and changing information, and plan memory consolidation and evaluation based on the kinds of questions the agent must answer.

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• Retain user preferences across conversations
• Track people and entities consistently across sessions
• Retrieve facts valid at a specific point in time

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.

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

Develop and troubleshoot plugins that connect external memory services to Nexent. Define plugin settings, implement search and ingestion, map errors, test with simulated network responses, and verify deployment, authentication, and runtime monitoring.

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• Adding an external memory service to Nexent
• Reviewing an existing memory adapter
• Testing plugins without live service connections

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.

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Migrates Claude Code personal memory (the per-project memory/ directory) into tool-agnostic reference docs so other AI CLIs that auto-load AGENTS.md (Codex primarily) can read the same user profile and preferences. Use when the user says "migrate my memory", "my memory is locked to Claude Code", "make Codex/Cursor read my profile", or reports memory has grown bloated with content that should be shared across tools. Also use it to retire a project's auto memory entirely (turn it off, move everything into documents, archive the directory).

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Review the file-based memory store via the Agent Monitor Config Explorer API: the user and project CLAUDE.md plus per-project auto-memory files under ~/.claude/projects/<slug>/memory/*.md. Groups by project, shows the index (MEMORY.md) vs per-fact files, and flags stale or oversized facts. Reads /api/cc-config/memory and /api/cc-config/file?path=. Use when curating agent memory.

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Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memoryUse when "conversation memory, remember, memory persistence, long-term memory, chat history, memory, conversation, persistence, context, llm" mentioned.

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Configure and manage Claude Code persistent memory (CLAUDE.md, auto memory, rules) across sessions. Use when setting up project memory, organizing .claude/rules/, managing auto memory files, creating CLAUDE.md with imports, debugging memory loading, or advising on memory hierarchy and best practices.

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Audit, classify, and selectively forget stored memories. Covers memory enumeration and classification by type/age/access frequency, staleness detection for outdated references, fidelity checks using external anchors, a decision tree for selective withdrawal, tombstoned deaccession so removed content stays recoverable, counter-memory inoculation for failed strategies that would otherwise be re-derived, preemptive filtering rules for what should never become memories, and an audit trail so forgetting itself is reviewable. Use when memory has grown large and uncurated, when project state has shifted significantly since memories were written, when retrieval quality has degraded, or as periodic maintenance alongside manage-memory.

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Organize, extract, prune, and verify Claude Code persistent memory files. Covers MEMORY.md as a concise index, topic extraction to dedicated files, staleness detection, accuracy verification against project state, the dual 200-line / 25KB load cap, and reachability of topic files from the index. Use when MEMORY.md is approaching either load cap, after a session produces durable insights worth preserving, when a topic section has grown beyond 10-15 lines and should be extracted, when project state has changed and memory entries may be stale, or before and after rewriting the index so that no topic file loses its only pointer.

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