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dingtalk-task-stats

Consolidates DingTalk AI Table task data and staff hours into Markdown reports.

1|2|Updated Feb 28, 2026
Search Tags:#mcp#reporting#task-tracking#data-aggregation#dingtalk#ai-table#workforce-analysis
One-click install
npx skills add https://github.com/zhangdszq/vk-skills --skill dingtalk-task-stats
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dingtalk-task-stats
Source: https://github.com/zhangdszq/vk-skills/tree/main/dingtalk-task-stats
Command: npx skills add https://github.com/zhangdszq/vk-skills --skill dingtalk-task-stats

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Consolidates and analyzes DingTalk AI Table tasks and staff hours across teams to expose workload and progress insights.

Core Features & Use Cases

  • Connects to two MCP services (dingtalk-ai-table and dingtalk-contacts) to fetch tasks and map employee IDs to real names.
  • Generates per-person and team-level statistics for task counts, estimated vs actual hours, and status distributions.
  • Produces Markdown reports or dashboards for team leads and PMs, enabling sprint planning and resource allocation.

Quick Start

Install mcporter, configure both MCP servers in config/mcporter.json, and run a workflow to pull data, map IDs to names, and generate a team report.

Frequently Asked Questions about dingtalk-task-stats

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate DingTalk task stats and team time tracking reporting?▼

Automate DingTalk task stats by configuring two MCP services in mcporter to fetch AI Table tasks and contacts, resolving employee IDs to names, and aggregating data into a Markdown report for workload insights.

How does DingTalk AI Table data aggregation map employee IDs to real names?▼

DingTalk AI Table data aggregation maps employee IDs to names by connecting to the dingtalk-contacts MCP service. This resolves raw staff identifiers into readable names for per-person time tracking reports.

Do I need mcporter to generate per-person task statistics from DingTalk?▼

Yes, you need mcporter to generate per-person task statistics. You must configure both dingtalk-ai-table and dingtalk-contacts MCP servers in config/mcporter.json before running the data aggregation workflow.

What is the best way to track estimated versus actual hours across DingTalk teams?▼

Track estimated versus actual hours by fetching task data through the DingTalk AI Table MCP service. The workflow generates team-level statistics comparing hour estimates to actual logged time for resource allocation.

Can I generate sprint planning dashboards from DingTalk task status distributions?▼

Generate sprint planning dashboards by analyzing DingTalk task status distributions. The workflow aggregates task counts and statuses into Markdown reports, exposing team progress and workload insights for PMs.

Why are my DingTalk workload reports showing unresolved employee IDs?▼

Unresolved employee IDs in DingTalk workload reports indicate the dingtalk-contacts MCP service is not properly configured in config/mcporter.json. Ensure both MCP service configurations are active before running the workflow.

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