spark-recipe-calendar-audit

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Chinese

Recipe: Calendar Audit

操作指南：日历审计

Analyze meeting load over a week or custom time range. Count meetings, estimate total hours, identify the busiest days, flag back-to-back chains, and surface free blocks.

Prerequisite: Read the

use-spark

base skill for command reference and filter syntax.

Access level required: read-only.

分析一周或自定义时间段内的会议负载。统计会议数量、估算总时长、识别最繁忙的日子、标记连续会议链，并显示空闲时段。

前提条件：阅读

use-spark

基础技能文档以了解命令参考和过滤语法。

所需权限级别：只读。

Steps

步骤

Step 1: Pull events for the period

步骤1：提取指定时间段的事件

For the current week:

bash

spark events --week

For a custom range:

bash

spark events --start 2026-04-13 --end 2026-04-17

Record each event's date, start time, end time, and title.

针对当前周：

bash

spark events --week

针对自定义时间段：

bash

spark events --start 2026-04-13 --end 2026-04-17

记录每个事件的日期、开始时间、结束时间和标题。

Step 2: Check free time

步骤2：查看空闲时间

bash

spark availability --week

Or for the same custom range:

bash

spark availability --start 2026-04-13 --end 2026-04-17

This shows free slots within working hours (08:00-20:00), skipping weekends and events marked "free."

bash

spark availability --week

或针对相同的自定义时间段：

bash

spark availability --start 2026-04-13 --end 2026-04-17

该命令会显示工作时间（08:00-20:00）内的空闲时段，跳过周末和标记为“空闲”的事件。

Step 3: Compute metrics

步骤3：计算指标

From the events list, calculate:

Total meetings: count of events
Total meeting hours: sum of all event durations
Per-day breakdown: meetings and hours per day
Busiest day: the day with the most meeting hours
Lightest day: the day with the fewest meetings (best for deep work)
Back-to-back chains: sequences of 2+ meetings with no gap between them
Longest free block: the largest contiguous free window from the availability output

从事件列表中计算：

会议总数：事件的数量
总会议时长：所有事件时长的总和
每日细分：每天的会议数量及时长
最繁忙日：会议时长最多的一天
最轻松日：会议数量最少的一天（最适合深度工作）
连续会议链：2场及以上无间隔的会议序列
最长空闲时段：从可用性输出中获取的最大连续空闲窗口

Step 4: Check across calendars (optional)

步骤4：跨日历检查（可选）

If the user has multiple calendars or accounts:

bash

spark events --week --in user@work.com
spark events --week --in user@personal.com

Compare meeting loads across contexts.

如果用户拥有多个日历或账户：

bash

spark events --week --in user@work.com
spark events --week --in user@personal.com

对比不同场景下的会议负载。

Step 5: Present the audit

步骤5：呈现审计结果

Report:

Summary: N meetings totaling X hours this week (Y% of working hours)
Per day: table of meetings and hours per day, flagging the busiest and lightest
Back-to-back: list any chains of consecutive meetings (flag chains of 3+)
Free blocks: the longest free windows available for deep work
Observations: any patterns worth noting (e.g., mornings packed but afternoons free, one day completely booked)

报告内容：

摘要：本周共N场会议，总时长X小时（占工作时间的Y%）
每日情况：每日会议数量及时长的表格，标记最繁忙和最轻松的日子
连续会议：列出所有连续会议链（重点标记3场及以上的链）
空闲时段：可用于深度工作的最长空闲窗口
观察结论：值得关注的模式（例如：上午会议密集但下午空闲、某天被完全占满）

Tips

小贴士

Run this on Monday to plan the week, or Friday to review how the week went.
Back-to-back chains of 3+ meetings are worth flagging - they leave no buffer for breaks or follow-ups.
The ratio of meeting hours to total working hours (assume 8-10 hours/day) gives a quick "meeting load" percentage.
For a forward-looking audit, use
```
--start
```
and
```
--end
```
with next week's dates.
Events marked "free" in the calendar don't count against availability - they won't inflate the meeting load.
Combine with
```
recipe-schedule-meeting
```
to find the best slots for new meetings in a busy week.
If the user has recurring meetings, patterns will be consistent week-to-week. Focus commentary on what's unusual.

周一运行此操作以规划本周，或周五运行以复盘本周情况。
3场及以上的连续会议链值得重点标记——它们没有留出休息或跟进工作的缓冲时间。
会议时长与总工作时间（假设每天8-10小时）的比值可快速得出“会议负载”百分比。
若要进行前瞻性审计，使用
```
--start
```
和
```
--end
```
参数指定下周的日期。
日历中标记为“空闲”的事件不会占用可用时间——它们不会虚增会议负载。
结合
```
recipe-schedule-meeting
```
操作指南，在繁忙的一周中找到安排新会议的最佳时段。
如果用户有 recurring meetings（ recurring meetings保留原文），每周的模式会保持一致。重点评论异常情况。