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 agentmods add skills/nongjun/feishu-cursor-claw/apple-notes-syncnpx skills add nongjun/feishu-cursor-claw --skill apple-notes-syncgit clone --depth 1 https://github.com/nongjun/feishu-cursor-clawWrote 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/nongjun/feishu-cursor-claw/apple-notes-sync)<a href="https://agentmods.dev/skills/nongjun/feishu-cursor-claw/apple-notes-sync"><img src="https://agentmods.dev/badge/skills/nongjun/feishu-cursor-claw/apple-notes-sync.svg" alt="Measured on agentmods" 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 | $0.00055 | $0.00717 |
| Opus 5 | $0.00028 | $0.00358 |
| Sonnet 5 | $0.00011 | $0.00143 |
| Haiku 4.5 | $0.00006 | $0.00072 |
Grade A, and why
apple-notes-sync 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 5d 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.
What it actually says
Mac 备忘录向量化同步
前置条件
- macOS 系统
- 备忘录应用中有内容
relay-bot/sync-apple-notes.ts脚本存在
执行步骤
1. 同步备忘录
bun ~/Documents/Ai管理的文件夹/relay-bot/sync-apple-notes.ts
首次运行需要授权（系统弹窗），用户需允许访问备忘录。
备忘录数量大（>500 条）时先用 --limit 测试：
bun ~/Documents/Ai管理的文件夹/relay-bot/sync-apple-notes.ts --limit 50
2. 等待完成
- 约 1000 条需要 15-20 分钟
- 增量同步自动跳过未修改的备忘录
- 输出目录：
~/Documents/Ai管理的文件夹/apple-notes/
3. 加入向量索引
bun ~/Documents/Ai管理的文件夹/relay-bot/memory-tool.ts index
4. 验证搜索
bun ~/Documents/Ai管理的文件夹/relay-bot/memory-tool.ts search "关键词"
脚本参数
| 参数 | 说明 | 示例 |
|---|---|---|
--folder |
只同步指定文件夹 | --folder "工作" |
--limit |
限制每个文件夹处理数量 | --limit 100 |
常见问题
数据库锁定 (database is locked)
lsof ~/Documents/Ai管理的文件夹/.memory.sqlite
kill <PID> # 杀掉非 server.ts 的进程
AppleScript 超时
备忘录太多导致超时。用 --limit 分批处理。
授权被拒绝
系统设置 → 隐私与安全性 → 自动化 → 允许终端/Cursor 访问 Notes
定时同步（可选）
在 cron-jobs.json 添加：
{
"id": "apple-notes-sync",
"name": "每日同步 Mac 备忘录",
"enabled": true,
"schedule": { "kind": "cron", "expr": "0 3 * * *", "tz": "Asia/Shanghai" },
"message": "执行 Mac 备忘录同步：\n1. 运行 sync-apple-notes.ts\n2. 运行 memory-tool.ts index\n3. 汇报同步结果"
}
输出结构
apple-notes/
├── Notes/ # 默认文件夹
│ ├── 备忘录1.md
│ └── 备忘录2.md
├── To Do/ # 待办文件夹
└── .sync-manifest.json # 同步状态记录
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.
- 5d ago First seen · 96 lines · 55 tokens per session scan A 63c6004c3a38
apple-notes-sync is a skill published in the GitHub repository nongjun/feishu-cursor-claw (14 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 717 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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docs-adr
Create and maintain lightweight Architecture Decision Records as agent-readable decision memory — what was decided, why, and which alternatives were rejected. Use when "record this decision", "set up ADRs", "the agent keeps suggesting Y again". Docs vs code drift → plan-docs-sync. Session state → handoff.
docs-domain-modeling
Build and sharpen a project's domain model — a CONTEXT.md glossary and ubiquitous language. Use when pinning down terminology, or the agent "uses the wrong words". Repo decision-memory system (INDEX.md, rejected alternatives) → docs-adr.
checkpoint
Save a session checkpoint — what was done, what's next, any blockers.
resume
Resume from last checkpoint — load full context and continue where you left off.
note
Quick note — save a decision, observation, or thought to persistent memory.