pm-report

pm-report is a skill for Claude Code from konglong87/superPM. It costs 44 tokens per session (2,312 once invoked), scanned A, original, MIT.

A guided process for collecting user feedback and producing data reports, including daily, weekly, monthly, special-topic, and feedback summaries. It is designed for Chinese-language project workflows.

In plain words
What is it for?
Use it to prepare reports from figures such as active users, revenue, average revenue per user, conversion rates, and user feedback.
Why use it?
It helps organize the report type, available metrics, comparisons, and trends before writing a report.

Skill for Claude Code

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

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

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.

agentmods
npx agentmods add skills/konglong87/superpm/pm-report
Any agent
npx skills add konglong87/superPM --skill pm-report
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-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/konglong87/superpm/pm-report.svg)](https://agentmods.dev/skills/konglong87/superpm/pm-report)
Your own site
<a href="https://agentmods.dev/skills/konglong87/superpm/pm-report"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-report.svg" alt="Measured on agentmods" height="20"></a>
Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,312 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00044 $0.02312
Opus 5 $0.00022 $0.01156
Sonnet 5 $0.00009 $0.00462
Haiku 4.5 $0.00004 $0.00231

Measured 6d ago against content hash dc8b1171383a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

pm-report 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 6d 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-report/SKILL.md · 303 lines

How it starts

The opening of the file, as written. The whole thing — 303 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/数据报告
mkdir -p docs/03-增长迭代/用户反馈

echo "📊 数据报告与用户反馈工具已启动"

# 检查数据指标体系
if [ -f "docs/02-方案设计/数据指标体系.md" ]; then
  echo "✅ 数据指标体系 - 已找到"
else
  echo "⏳ 数据指标体系 - 未找到(建议先执行 /pm-data)"
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: 选择报告类型

使用 AskUserQuestion 询问:

📊 选择报告类型

A) 日报(核心指标概览) B) 周报(周度数据总结) C) 月报(月度数据分析) D) 专项报告(特定主题分析,如转化率分析) E) 用户反馈整理(收集和分类用户反馈) F) 其他(请手动输入)

💡 提示:

  • 日常监控 → 日报
  • 团队同步 → 周报
  • 管理层汇报 → 月报
  • 问题定位 → 专项报告

记录到变量 REPORT_TYPE


步骤 2: 收集数据

基于数据指标体系或手动输入,收集关键指标数据。

📈 指标数据采集

请提供以下核心指标数据(如无法提供,可跳过):

用户指标

  • DAU(日活跃用户数):[输入]
  • MAU(月活跃用户数):[输入]
  • 新增用户数:[输入]

业务指标

  • GMV/营收:[输入]
  • ARPU(每用户平均收入):[输入]

转化指标

  • 整体转化率:[输入]
  • 各环节转化率:[输入]

A) 我有完整数据,逐项输入 B) 我只有部分数据,先填能填的 C) 暂无数据,只做趋势分析


步骤 3: 数据分析

📊 数据分析:

对比分析

  • 环比(对比上期):{[数据]}
  • 同比(对比去年同期):{[数据]}
  • 目标达成率:{[数据]}

趋势判断

  • 上升趋势:{指标} 持续上升
  • 下降趋势:{指标} 需要关注
  • 稳定状态:{指标} 在正常范围

异常识别

  • {指标1}:{描述异常}
  • {指标2}:{描述异常}

是否需要深入分析某个异常?


步骤 4: 用户反馈整理(可选)

如果选择了"用户反馈整理":

💬 用户反馈来源:

A) 应用商店评价 B) 客服工单 C) 用户访谈/调研 D) 社交媒体(微博/知乎) E) 内部反馈(运营/销售) F) 以上多项

反馈分类

  • Bug/故障:[X]条
  • 功能建议:[X]条
  • 体验问题:[X]条
  • 投诉/不满:[X]条
  • 表扬:[X]条

高频关键词:{关键词1}、{关键词2}、{关键词3}


步骤 5: 输出报告

根据报告类型,使用 Write 生成对应文档。

报告通用结构

# {产品名称} - {报告类型} - {日期}

## 一、核心指标总览

| 指标 | 本期 | 上期 | 环比 | 目标 | 达成率 |
|------|------|------|------|------|--------|
| DAU | [X] | [X] | ±X% | [X] | X% |
| 新增用户 | [X] | [X] | ±X% | [X] | X% |
| GMV | [X] | [X] | ±X% | [X] | X% |
| 转化率 | X% | X% | ±Xpp | X% | X% |

## 二、数据趋势分析

### 2.1 核心指标趋势
{趋势描述}

### 2.2 关键变化说明
- {变化1}:{原因分析}
- {变化2}:{原因分析}

## 三、异常说明

| 异常指标 | 表现 | 原因 | 处理状态 |
|---------|------|------|---------|
| {指标} | {异常描述} | {初步判断} | 处理中/已解决 |

## 四、改进建议

1. {建议1}
2. {建议2}
3. {建议3}

---

**生成时间**: {时间戳}
**数据来源**: {数据来源}

Read the full file on GitHub · 303 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. 6d ago First seen · 303 lines · 44 tokens per session scan A dc8b1171383a

Subscribe to this mod's changes

pm-report is a skill published in the GitHub repository konglong87/superPM (61 stars, last pushed 2d ago), licensed MIT. It adds 44 tokens to every session and 2,312 once invoked, about $0.0002 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.

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