sprint-review — for Claude Code sprint-review, rhesis, community, for Claude Code, ide skills, generative-ai, llm-evaluation, llm-evaluation-framework, llmops, open-source

v1.0.0
GitHub

关于此技能

适用场景： Ideal for AI agents that need generate a markdown changelog from github prs for sprint review meetings. 本地化技能摘要： Bring engineers, PMs, and domain experts together to generate tests, simulate (adversarial) conversations, and trace every failure to its root cause. It covers generative-ai, llm-evaluation, llm-evaluation-framework workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf

功能特性

Generate a markdown changelog from GitHub PRs for sprint review meetings.
Time range : last two weeks (14 days from today)
Author : the current GitHub user -- detect automatically via gh api user --jq .login
Both can be overridden if the user explicitly provides a different author or date.
Detect the current user (unless explicitly provided):

# 核心主题

for Claude Code generative-ai llm-evaluation llm-evaluation-framework llmops open-source
rhesis-ai rhesis-ai
[312]
[24]
更新于: 4/16/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
53
Canonical Locale
en
Detected Body Locale
en

适用场景： Ideal for AI agents that need generate a markdown changelog from github prs for sprint review meetings. 本地化技能摘要： Bring engineers, PMs, and domain experts together to generate tests, simulate (adversarial) conversations, and trace every failure to its root cause. It covers generative-ai, llm-evaluation, llm-evaluation-framework workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf

核心价值

推荐说明： sprint-review helps agents generate a markdown changelog from github prs for sprint review meetings. Bring engineers, PMs, and domain experts together to generate tests, simulate (adversarial) conversations, and

适用 Agent 类型

适用场景： Ideal for AI agents that need generate a markdown changelog from github prs for sprint review meetings.

↓ 赋予的主要能力 · sprint-review

适用任务： Applying Generate a markdown changelog from GitHub PRs for sprint review meetings
适用任务： Applying Time range : last two weeks (14 days from today)
适用任务： Applying Author : the current GitHub user -- detect automatically via gh api user --jq .login

! 使用限制与门槛

  • 限制说明： Requires repository-specific context from the skill documentation
  • 限制说明： Works best when the underlying tools and dependencies are already configured

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

评审后的下一步

先决定动作，再继续看上游仓库材料

Killer-Skills 的主价值不应该停在“帮你打开仓库说明”，而是先帮你判断这项技能是否值得安装、是否应该回到可信集合复核，以及是否已经进入工作流落地阶段。

安装路径

先进入安装与验证

如果这项技能值得继续，下一步应该先确认安装命令、CLI 写入路径与环境验证。
可信复核

回到可信合集再做一次复核

如果你还在比较不同技能或供应方，先回到可信合集做二次判断，而不是继续放大仓库噪音。
工作流

如果要进团队流转，转到工作流集合

当你的目标已经不是单个技能，而是团队协作、审批和可重复执行，就应该转到工作流合集继续比较。
实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致，便于搜索引擎理解页面内容。

? FAQ

sprint-review 是什么？

适用场景： Ideal for AI agents that need generate a markdown changelog from github prs for sprint review meetings. 本地化技能摘要： Bring engineers, PMs, and domain experts together to generate tests, simulate (adversarial) conversations, and trace every failure to its root cause. It covers generative-ai, llm-evaluation, llm-evaluation-framework workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf

如何安装 sprint-review？

运行命令：npx killer-skills add rhesis-ai/rhesis/sprint-review。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

sprint-review 适用于哪些场景？

典型场景包括：适用任务： Applying Generate a markdown changelog from GitHub PRs for sprint review meetings、适用任务： Applying Time range : last two weeks (14 days from today)、适用任务： Applying Author : the current GitHub user -- detect automatically via gh api user --jq .login。

sprint-review 支持哪些 IDE 或 Agent？

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

sprint-review 有哪些限制？

限制说明： Requires repository-specific context from the skill documentation；限制说明： Works best when the underlying tools and dependencies are already configured。

↓ 安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行：npx killer-skills add rhesis-ai/rhesis/sprint-review。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    sprint-review 已启用，可立即在当前项目中调用。

! 参考页模式

此页面仍可作为安装与查阅参考，但 Killer-Skills 不再把它视为主要可索引落地页。请优先阅读上方评审结论，再决定是否继续查看上游仓库说明。

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

sprint-review

安装 sprint-review，这是一款面向AI agent workflows and automation的 AI Agent Skill。查看评审结论、使用场景与安装路径。

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Sprint Review

Generate a markdown changelog from GitHub PRs for sprint review meetings.

Defaults

  • Time range: last two weeks (14 days from today)
  • Author: the current GitHub user -- detect automatically via gh api user --jq .login

Both can be overridden if the user explicitly provides a different author or date.

Workflow

  1. Detect the current user (unless explicitly provided):
bash
1gh api user --jq .login
  1. Collect PRs using GitHub CLI (default: last 14 days):
bash
1gh pr list --author <username> --state all --search "created:>=<date>" --limit 100 \
2  --json number,title,state,createdAt,body,url \
3  | jq -r '.[] | "\(.number)|\(.title)|\(.state)|\(.createdAt)|\(.url)"'

  1. Fetch PR bodies for context on what each PR does (use --json body).

  2. Group PRs into two sections:

    • Features -- new capabilities, refactors, new providers, new APIs
    • Fixes -- bug fixes, dependency patches, config corrections, minor chores

  3. Consolidate similar PRs under a single description when they share the same goal (e.g. two PRs making different parts of the SDK async-first).

  4. Write the markdown file to docs/changelog-<username>.md using this format:

markdown
1## PR Changelog -- <username> (<start date> -- <end date>)
2
3### Features
4
5**Short heading**
6
7One-to-two sentence description.
8
9- [#<number> -- <title>](<url>)
10- [#<number> -- <title>](<url>) *(open/draft if not merged)*
11
12### Fixes
13
14**Short heading**
15
16One sentence description.
17
18- [#<number> -- <title>](<url>)

Formatting rules

  • Section headings: ### for Features / Fixes
  • Entry headings: bold text (not a markdown heading)
  • Descriptions: 1-2 sentences max, focus on what changed and why it matters
  • PR links: bulleted list with #<number> -- <title> as link text
  • Mark non-merged PRs with (open) or (draft)
  • No emojis

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