Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add L-LesterYu/OpenClaw-hot-skills-zh --skill memory-setup-zhgit clone --depth 1 https://github.com/L-LesterYu/OpenClaw-hot-skills-zhWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/memory-setup-zh)<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/memory-setup-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/memory-setup-zh/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/memory-setup-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/memory-setup-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00064 | $0.01249 |
| Opus 5.5 | $0.00026 | $0.00500 |
| Sonnet 5.5 | $0.00013 | $0.00250 |
| Haiku 4.5 | $0.00006 | $0.00125 |
Grade A, and why
memory-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
记忆设置技能
让你的 Agent 从金鱼变成大象。本技能帮助配置 Moltbot/Clawdbot 的持久化记忆功能。
快速设置
1. 在配置中启用记忆搜索
添加到 ~/.clawdbot/clawdbot.json（或 moltbot.json）：
{
"memorySearch": {
"enabled": true,
"provider": "voyage",
"sources": ["memory", "sessions"],
"indexMode": "hot",
"minScore": 0.3,
"maxResults": 20
}
}
2. 创建记忆目录结构
在工作区中创建：
workspace/
├── MEMORY.md # 长期精炼记忆
└── memory/
├── logs/ # 每日日志 (YYYY-MM-DD.md)
├── projects/ # 项目特定上下文
├── groups/ # 群聊上下文
└── system/ # 偏好设置、安装笔记
3. 初始化 MEMORY.md
在工作区根目录创建 MEMORY.md：
# MEMORY.md — 长期记忆
## 关于 [用户名]
- 关键信息、偏好、上下文
## 活跃项目
- 项目摘要和状态
## 决策与经验教训
- 做出的重要选择
- 吸取的教训
## 偏好
- 沟通风格
- 工具和工作流
配置选项说明
| 设置项 | 用途 | 推荐值 |
|---|---|---|
enabled |
启用记忆搜索 | true |
provider |
嵌入向量提供商 | "voyage" |
sources |
索引范围 | ["memory", "sessions"] |
indexMode |
索引时机 | "hot"（实时） |
minScore |
相关性阈值 | 0.3（值越低结果越多） |
maxResults |
最大返回片段数 | 20 |
提供商选项
voyage— Voyage AI 嵌入向量（推荐）openai— OpenAI 嵌入向量local— 本地嵌入向量（无需 API 密钥）
数据源选项
memory— MEMORY.md + memory/*.md 文件sessions— 历史会话记录both— 全部上下文（推荐）
每日日志格式
每天创建 memory/logs/YYYY-MM-DD.md：
# YYYY-MM-DD — 每日日志
## [时间] — [事件/任务]
- 发生了什么
- 做出的决策
- 需要跟进的事项
## [时间] — [另一个事件]
- 详细信息
Agent 指令（AGENTS.md）
将以下内容添加到 AGENTS.md 中以控制 Agent 行为：
## 记忆回忆
在回答关于过往工作、决策、日期、人物、偏好或待办事项的问题前：
1. 使用 memory_search 进行相关查询
2. 需要时使用 memory_get 提取具体行
3. 如果搜索后信心不足，说明已检查过记忆
故障排除
记忆搜索不工作？
- 检查配置中
memorySearch.enabled: true是否已设置 - 确认工作区根目录存在 MEMORY.md
- 重启网关：
clawdbot gateway restart
搜索结果不相关？
- 将
minScore降低到0.2以获取更多结果 - 将
maxResults增加到30 - 检查记忆文件中是否有有意义的内容
提供商报错？
- Voyage：在环境变量中设置
VOYAGE_API_KEY - OpenAI：在环境变量中设置
OPENAI_API_KEY - 如无 API 密钥，使用
local提供商
验证
测试记忆功能是否正常工作：
用户："你还记得关于 [过去的话题] 的什么事吗？"
Agent：[应该搜索记忆并返回相关上下文]
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 172 lines · 64 tokens per session scan A 15b7dcc08c5f
memory-setup is a skill published in the GitHub repository L-LesterYu/OpenClaw-hot-skills-zh (57 stars, last pushed 6mo ago), licensed MIT. It adds 64 tokens to every session and 1,249 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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agent-v3-memory-specialist
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Explain and apply the foundational LLM Wiki architecture and knowledge-management strategy. Use for setup, architecture, schema, or organization decisions; operational ingest/query/lint work uses dedicated skills.