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local-agent-memory-v1

Build, maintain, or improve a layered local memory system for OpenClaw-style agents using markdown files instead of database-backed memory. Use when creating or refining `MEMORY.md`, `memory/YYYY-MM-DD.md`, `memory/semantic/`, `memory/procedural/`, heartbeat-based memory consolidation, skeptical memory rules, strict write discipline, long-term memory governance, or file-based agent memory workflows in local/Termux/workspace-based setups.

作者: admin | 来源: ClawHub
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V 1.0.0
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local-agent-memory-v1

# Local Agent Memory v1 Build or refine a reliable file-based memory system for an agent. ## Core workflow 1. Create or inspect these layers: - `memory/YYYY-MM-DD.md` - `memory/semantic/` - `memory/procedural/` - `MEMORY.md` 2. Keep `MEMORY.md` lightweight and routing-oriented. 3. Put stable facts in semantic files. 4. Put repeatable methods in procedural files. 5. Treat memory as a hint/index layer, not unquestionable truth. 6. Re-verify current facts before taking real actions based on remembered information. 7. Write destination files first, then update `MEMORY.md` only if the change deserves long-term indexing. ## Decision rules ### Use daily memory for - new events - one-off attempts - temporary troubleshooting detail - anything not yet proven reusable ### Use semantic memory for - stable user preferences - durable environment facts - platform constraints - lasting architecture or governance decisions ### Use procedural memory for - repeatable workflows - checklists - maintenance routines - methods likely to be reused across sessions ## Maintenance pattern Run a lightweight dream/consolidation pass when memory starts to sprawl: - read `MEMORY.md` - read recent daily logs - identify repeated facts or workflows - extract stable facts into semantic memory - extract repeatable methods into procedural memory - prune low-value or duplicated summary lines from `MEMORY.md` Run a deeper pass for large daily logs or when the topic tree needs restructuring. ## Guardrails - Do not let `MEMORY.md` become a diary. - Do not promote everything that looks interesting. - Do not rely on stale remembered facts for real actions. - Do not mix memory maintenance with unrelated code changes unless the user asked for both. - Prefer a few clear topic files over many overlapping files. ## References Read these only as needed: - `references/architecture.md` for the memory model and core disciplines - `references/setup.md` for minimum structure and topic layout - `references/maintenance.md` for governance and consolidation rules

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skill ai

通过对话安装

该技能支持在以下平台通过对话安装:

OpenClaw WorkBuddy QClaw Kimi Claude

方式一:安装 SkillHub 和技能

帮我安装 SkillHub 和 local-agent-memory-v1-1775904721 技能

方式二:设置 SkillHub 为优先技能安装源

设置 SkillHub 为我的优先技能安装源,然后帮我安装 local-agent-memory-v1-1775904721 技能

通过命令行安装

skillhub install local-agent-memory-v1-1775904721

下载 Zip 包

⬇ 下载 local-agent-memory-v1 v1.0.0

文件大小: 3.59 KB | 发布时间: 2026-4-12 10:27

v1.0.0 最新 2026-4-12 10:27
Initial release: layered local memory, skeptical memory, strict write discipline, governance, and consolidation workflow

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