pm-retro

pm-retro is a skill for Claude Code from konglong87/superPM. It costs 52 tokens per session (2,470 once invoked), scanned A, original, MIT.

A retrospective workflow for reviewing a finished agile iteration, recording what happened, and choosing improvements for the next cycle.

In plain words
What is it for?
Use it to review completion rates, planned versus finished work, team feedback, lessons learned, and process improvements.
Why use it?
It gives the team a structured way to compare results with goals and turn feedback into concrete follow-up actions.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the super-pm plugin — 55 skills, 1 hook shipped together

Good fit Use it to review completion rates, planned versus finished work, team feedback, lessons learned, and process improvements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/konglong87/superpm/pm-retro
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add konglong87/superPM --skill pm-retro
Clone the repo
git clone --depth 1 https://github.com/konglong87/superPM

Made for: Claude Code.

Or install super-pm, the plugin that ships this one along with the rest of its 55 skills, 1 hook.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pm-retro

README.md
[![agentmods](https://agentmods.dev/badge/skills/konglong87/superpm/pm-retro.svg)](https://agentmods.dev/skills/konglong87/superpm/pm-retro)
Your own site
<a href="https://agentmods.dev/skills/konglong87/superpm/pm-retro"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-retro.svg" alt="Measured on agentmods" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,470 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.02470
Opus 5 $0.00026 $0.01235
Sonnet 5 $0.00010 $0.00494
Haiku 4.5 $0.00005 $0.00247

Measured 8d ago against content hash 98780c9b213e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

pm-retro scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/03-growth-iteration/pm-retro/SKILL.md · 326 lines

How it starts

The opening of the file, as written. The whole thing — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Preamble

bash "$(dirname "${BASH_SOURCE[0]}")/../../check-update.sh" 2>/dev/null || true
mkdir -p docs/03-增长迭代/迭代复盘

echo "📝 迭代复盘工具已启动"

# 检查迭代计划
if [ -f "docs/03-增长迭代/迭代计划.md" ]; then
  echo "✅ 迭代计划 - 已找到"
else
  echo "⏳ 迭代计划 - 未找到"
fi

# 检查迭代完成情况
if [ -f "docs/03-增长迭代/数据报告与用户反馈.md" ]; then
  echo "✅ 数据报告 - 已找到"
else
  echo "⏳ 数据报告 - 未找到"
fi

跨 Agent 交互规则

当流程要求与用户交互时:

  1. 如果当前环境支持 AskUserQuestion,使用 AskUserQuestion(最佳体验)。
  2. 如果当前环境不支持 AskUserQuestion,必须用普通聊天消息提出同样问题。
  3. 一次只问一个问题。
  4. 提问后必须停止当前回合,等待用户回答(STOP and WAIT)。
  5. 不得在用户回答前生成文档、写入 docs。
  6. 已有 docs 文件不能替代本轮用户回答。

执行流程

步骤 1: 复盘准备

使用 AskUserQuestion 询问:

🎯 迭代复盘准备

迭代信息

  • 迭代编号:第X次迭代
  • 迭代周期:YYYY-MM-DD 至 YYYY-MM-DD
  • 参与角色:产品、开发、设计、QA、运营(可多选)

迭代目标回顾

本次迭代原定的核心目标是什么?

A) 目标1:{描述} B) 目标2:{描述} C) 目标3:{描述} D) 没有明确目标

记录到变量 ITERATION_INFO


步骤 2: 目标达成评估

📊 目标达成评估

目标1:{目标描述}

  • 完成情况:{X}%
  • 是否达成:✅/🟡/❌
  • 说明:{完成/未完成的原因}

目标2:{目标描述}

  • 完成情况:{X}%
  • 是否达成:✅/🟡/❌
  • 说明:{完成/未完成的原因}

整体完成率:{X}%

需求完成统计

优先级 计划 完成 未完成 完成率
P0 X X X X%
P1 X X X X%
P2 X X X X%

上述数据是否准确?


步骤 3: 收集团队反馈(KPT)

使用 AskUserQuestion 收集 KPT(Keep-Problem-Try):

📝 团队反馈收集(KPT模型)

Keep - 做得好的地方(值得继续保持)

示例:

  • 代码审查流程规范,Bug率降低
  • 每日站会效率高
  • 设计评审及时

请列举做得好的地方(每行一个,输入"完成"结束):

收集到列表 KEEP_ITEMS

Problem - 需要改进的问题

示例:

  • 需求变更频繁,影响开发节奏
  • 测试时间不足,线上Bug较多
  • 跨部门沟通不及时

请列举需要改进的问题(每行一个,输入"完成"结束):

收集到列表 PROBLEM_ITEMS

Try - 尝试的行动方案

针对上述问题,尝试以下行动:

示例:

  • 建立需求变更审批机制
  • 预留20%测试缓冲时间
  • 建立跨部门沟通群,每天同步进展

请列举尝试的行动(每行一个,输入"完成"结束):

收集到列表 TRY_ITEMS


步骤 4: 根因分析

对 TOP 问题(团队反馈最多的)进行根因分析:

🔍 根因分析

TOP问题:{问题描述}

5 Whys 分析

问题:{问题}
Why 1:{直接原因}
Why 2:{深层原因}
Why 3:{根本原因}
Why 4:{系统性原因}
Why 5:{根因结论}

根因:{根因结论}

解决方案

  1. {短期措施} - 立即执行
  2. {长期措施} - 持续改进
  3. {预防措施} - 防止复发

Read the full file on GitHub · 326 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 326 lines · 52 tokens per session scan A 98780c9b213e

Subscribe to this mod's changes

pm-retro is a skill published in the GitHub repository konglong87/superPM (62 stars, last pushed 4d ago), licensed MIT. It adds 52 tokens to every session and 2,470 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.