spark-recipe-team-workload

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Recipe: Team Workload

方案：团队工作量审计

Deep audit of how work is distributed across a team. Surfaces per-member assignment loads, items you've delegated, unassigned work, and imbalances.

Prerequisite: Read the

use-spark

base skill for command reference and filter syntax.

Access level required: read-only.

深入审计团队内的工作分配情况，呈现成员个人任务量、你已委派的任务、未分配工作以及工作量失衡问题。

前置条件： 阅读

use-spark

基础技能文档，了解命令参考和过滤语法。

所需权限： 只读权限。

Steps

步骤

Step 1: Get the team overview

步骤1：获取团队概览

bash

spark team "Team Name"

Note the member list, shared inboxes, and the assignment summary. This gives you the high-level distribution.

bash

spark team "Team Name"

记录成员列表、共享收件箱以及任务分配摘要，这能让你了解整体分配情况。

Step 2: Review per-member assignments

步骤2：查看成员个人任务分配

For each team member, pull their current assignments:

bash

spark emails --filter "assigned_to:alice@co.com"
spark emails --filter "assigned_to:bob@co.com"
spark emails --filter "assigned_to:carol@co.com"

Note the count and scan subjects/dates to spot stale items (old assignments that may be stuck).

针对每位团队成员，获取他们当前的任务：

bash

spark emails --filter "assigned_to:alice@co.com"
spark emails --filter "assigned_to:bob@co.com"
spark emails --filter "assigned_to:carol@co.com"

记录任务数量，浏览主题和日期以识别停滞任务（可能被搁置的旧任务）。

Step 3: Check what you've delegated

步骤3：检查你已委派的任务

bash

spark emails --filter "assigned_by:me"

These are items you assigned to others. Cross-reference with per-member lists to see which are still open.

bash

spark emails --filter "assigned_by:me"

这些是你分配给他人的任务，与成员个人任务列表交叉核对，查看哪些仍处于未完成状态。

Step 4: Find unassigned work

步骤4：查找未分配工作

bash

spark emails --filter "assigned_to:unassigned"

If the team uses shared inboxes, also check each one:

bash

spark emails shared@co.com:Inbox --filter "assigned_to:unassigned"

bash

spark emails --filter "assigned_to:unassigned"

如果团队使用共享收件箱，还需检查每个共享收件箱：

bash

spark emails shared@co.com:Inbox --filter "assigned_to:unassigned"

Step 5: Check open vs. done in shared inboxes

步骤5：检查共享收件箱中的待办与已完成任务

bash

spark emails --filter "is:shared_inbox_open"
spark emails --filter "is:shared_inbox_done"

The ratio of open to done gives a sense of whether the team is keeping up.

bash

spark emails --filter "is:shared_inbox_open"
spark emails --filter "is:shared_inbox_done"

待办与已完成任务的比例能反映团队是否跟得上工作进度。

Step 6: Present the workload report

步骤6：提交工作量报告

Summarize:

Per member: assignment count and any notably old items
Imbalances: flag members with significantly more or fewer assignments than average
Delegated by you: N items still open, any that look overdue
Unassigned: M items with no owner
Throughput: open vs. done ratio across shared inboxes

总结内容包括：

成员个人情况： 任务数量以及任何明显的旧任务
工作量失衡： 标记任务量显著高于或低于平均值的成员
你委派的任务： 仍有N项未完成，其中是否有逾期任务
未分配工作： M项无负责人的任务
处理效率： 共享收件箱中待办与已完成任务的比例

Tips

提示

Run this weekly to catch imbalances before they become problems.
The
```
team
```
command's assignment summary is a quick snapshot; the per-member
```
emails
```
queries give the full picture.
Stale assignments (older than 7-14 days) are worth flagging - they may be stuck or forgotten.
```
assigned_by:me
```
is useful for managers and leads who delegate frequently.
Compare this week's numbers to last week's (if you track them) to spot trends.
Combine with
```
recipe-shared-inbox-status
```
for a shared-inbox-focused view, or use this recipe for the broader team picture.
For large teams, focus on outliers rather than reporting every member - highlight who's overloaded and who has bandwidth.

每周执行一次此审计，在失衡问题恶化前及时发现。
```
team
```
命令的任务分配摘要是快速快照，而针对成员个人的
```
emails
```
查询能提供完整信息。
停滞任务（超过7-14天）值得关注——它们可能已被搁置或遗忘。
```
assigned_by:me
```
对经常委派任务的经理和负责人很有用。
将本周数据与上周数据（如果有记录）对比，识别趋势。
可结合
```
recipe-shared-inbox-status
```
获取聚焦共享收件箱的视图，或使用本方案了解更全面的团队情况。
对于大型团队，重点关注异常情况而非每位成员——突出任务过载和有空闲带宽的成员。