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 malue-ai/dazee-small --skill daily-briefinggit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/daily-briefing)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/daily-briefing"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/daily-briefing/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/malue-ai/dazee-small/daily-briefing"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/daily-briefing.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 | $0.00022 | $0.00591 |
| Opus 5 | $0.00011 | $0.00296 |
| Sonnet 5 | $0.00004 | $0.00118 |
| Haiku 4.5 | $0.00002 | $0.00059 |
Grade A, and why
daily-briefing 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 12d 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
每日简报
生成个性化的每日简报，整合天气、日程、待办、新闻要点，帮助用户快速了解今日安排。
使用场景
- 用户说「今天有什么安排」「早安」「帮我看看今天的日程」
- 用户在早上打开应用，希望快速了解当天概况
- 用户说「今天需要关注什么」
执行方式
按以下模块逐步收集信息，然后整合为简报。
信息收集流程
1. 天气 → 调用 weather skill（wttr.in）
2. 日历 → 调用 apple-calendar / outlook-cli / gog（按平台）
3. 待办 → 调用 apple-reminders / things-mac / trello / todoist（按用户配置）
4. 新闻 → 调用搜索类 Skill 搜索当日热点（可选）
每个模块独立获取，某个模块失败不影响其他模块。
简报模板
# 早安，[用户名]！ ☀️
**[日期] [星期]**
---
## 🌤️ 天气
[城市]：[天气状况] [温度]，[湿度] [风速]
今日建议：[穿衣/出行建议]
## 📅 今日日程
| 时间 | 事项 |
|---|---|
| 09:00 | [事项1] |
| 14:00 | [事项2] |
（无日程时显示：今天没有预约的日程，可以自由安排 ✨）
## ✅ 待办事项
- [ ] [任务1]（截止：今天）
- [ ] [任务2]（截止：明天）
（共 X 项待办，Y 项今日到期）
## 📰 今日要闻（可选）
1. [新闻标题1]
2. [新闻标题2]
个性化
- 通过 MEMORY.md 记住用户偏好（城市、关注领域、常用待办工具）
- 首次使用时询问用户所在城市和偏好
- 根据用户反馈调整简报内容（如关闭新闻模块）
输出规范
- 语气亲切但简洁，像朋友打招呼
- 所有时间使用用户本地时区
- 日程按时间排序
- 待办按紧急程度排序（今日到期 > 明日 > 本周）
- 整体长度控制在一屏内可读完
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.
- 12d ago First seen · 82 lines · 22 tokens per session scan A cd41b451d1c4
daily-briefing is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 22 tokens to every session and 591 once invoked, about $0.0001 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 2026-08-31.
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