yunxiao-req-review-stats

Aggregate sprint review conclusions into a Markdown report with per-assignee metrics.

3|Updated Apr 2, 2026
One-click install
npx skills add https://github.com/weiran-tech/agent-skills --skill yunxiao-req-review-stats
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: yunxiao-req-review-stats
Source: https://github.com/weiran-tech/agent-skills/tree/main/skills/yunxiao-req-review-stats
Command: npx skills add https://github.com/weiran-tech/agent-skills --skill yunxiao-req-review-stats

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

云效项目迭代中的需求评审结果统计与汇总变得繁琐。本技能自动聚合评审结论、计算总需求、通过/未通过数量,以及按负责人分布,帮助团队快速评估迭代质量。

Core Features & Use Cases

  • 统计聚合:提取迭代中的所有需求工作项,计算总数、通过数、未通过数和通过率。
  • 责任分布:按负责人汇总工作项数量及通过情况,便于资源调度。
  • 输出清单:生成未通过项清单及汇总表,提供任务链接以便后续跟进。

真实场景:在迭代结束后,团队运行此技能即可获得本次迭代的评审概览和待处理项列表。

Quick Start

直接将 MCP 转换后的 JSON 数据与该迭代标识作为输入运行脚本以生成迭代评审报告。

Frequently Asked Questions about yunxiao-req-review-stats

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

FAQPage Schema
How do I generate sprint review statistics for a Yunxiao project iteration?

To generate sprint review statistics, provide the Yunxiao sprint ID or name along with MCP-formatted requirement data. The tool aggregates review conclusions to compute total, pass, and fail counts, outputting a per-assignee metrics report.

What metrics are included in Yunxiao sprint review reports?

Yunxiao sprint review reports include total requirements, pass count, fail count, and pass rate. They also provide per-assignee work item distributions and a checklist of failed items with task links for follow-up.

Can I analyze requirement review conclusions by assignee for cloud project sprints?

Yes, you can analyze requirement review conclusions by assignee. The tool parses sprint data and summarizes work item quantities and pass/fail statuses for each assignee, enabling effective resource allocation and evaluation.

Do I need MCP-formatted JSON data to use the yunxiao-req-review-stats Skill?

Yes, MCP-formatted JSON data is required as input. You must run the script by passing the converted JSON data alongside the sprint identifier to generate the iteration review report.

How does the requirement review aggregation process work for project management iterations?

The aggregation process works by parsing MCP-formatted data, converting it to a stats-friendly JSON format, and calculating review outcomes. It then generates a Markdown report summarizing per-assignee metrics and failed items for the iteration.

What is the best way to track unpassed requirements after a Yunxiao sprint review?

The best way to track unpassed requirements is to review the generated failed item checklist. The report outputs a summary table with direct task links for each unpassed requirement, ensuring efficient follow-up actions.