pm-funnel

pm-funnel is a skill for Claude Code from konglong87/superPM. It costs 59 tokens per session (4,224 once invoked), scanned A, original, MIT.

A guide for analysing a user conversion funnel—the sequence of steps from first visit or use to a target action such as payment.

In plain words
What is it for?
Use it to map registration, purchase, activation, or retention journeys, calculate step-by-step conversion and drop-off rates, and propose improvements.
Why use it?
It shows where people leave the journey and helps identify which step may need improvement.

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 map registration, purchase, activation, or retention journeys, calculate step-by-step conversion and drop-off rates, and propose improvements.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/konglong87/superpm/pm-funnel.svg)](https://agentmods.dev/skills/konglong87/superpm/pm-funnel)
Your own site
<a href="https://agentmods.dev/skills/konglong87/superpm/pm-funnel"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-funnel.svg" alt="Measured on agentmods" height="20"></a>
Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,224 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 $0.00059 $0.04224
Opus 5 $0.00030 $0.02112
Sonnet 5 $0.00012 $0.00845
Haiku 4.5 $0.00006 $0.00422

Measured 8d ago against content hash 2438ad79ba86, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

pm-funnel 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/05-product-strategy/pm-funnel/SKILL.md · 600 lines

How it starts

The opening of the file, as written. The whole thing — 600 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Preamble (run first)

bash "$(dirname "${BASH_SOURCE[0]}")/../../check-update.sh" 2>/dev/null || true
# 创建目录
mkdir -p docs/05-产品战略

# 检查是否有用户旅程地图作为输入
if [ -f "docs/01-需求调研/用户旅程地图.md" ]; then
  echo "✅ 检测到用户旅程地图,将基于此进行漏斗分析"
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: 定义转化漏斗

询问方式:使用 AskUserQuestion 逐个询问


问题 1: 业务场景

使用 AskUserQuestion 询问:

请问您要分析哪个业务场景的转化漏斗?

A) 注册转化漏斗(访客→注册用户) B) 购买转化漏斗(浏览→下单→支付) C) 激活转化漏斗(下载→注册→首次使用) D) 留存转化漏斗(新增→次日留存→7日留存) E) 其他(请手动输入)


问题 2: 漏斗步骤定义

根据问题1的场景,引导用户定义具体步骤:

示例(购买转化漏斗)

请确认购买转化漏斗的关键步骤

引导用户输入:

  1. 步骤1:[浏览商品详情页]
  2. 步骤2:[加入购物车]
  3. 步骤3:[进入结算页]
  4. 步骤4:[提交订单]
  5. 步骤5:[完成支付]

问题 3: 当前数据

针对每个步骤,收集当前数据:

使用 AskUserQuestion 询问:

步骤[1]:[浏览商品详情页]的用户数是多少?

引导用户输入每个步骤的用户数:

步骤 用户数 占比
步骤1 [X]万 100%
步骤2 [X]万 [X]%
步骤3 [X]万 [X]%
步骤4 [X]千 [X]%
步骤5 [X]千 [X]%

步骤 2: 计算转化率和流失率

计算公式

步骤转化率 = (下一步用户数 / 当前步骤用户数) × 100%
步骤流失率 = 100% - 步骤转化率
整体转化率 = (最后一步用户数 / 第一步用户数) × 100%

示例

步骤 用户数 步骤转化率 步骤流失率
浏览详情页 10,000 - -
加入购物车 3,000 30% 70%
进入结算页 2,100 70% 30%
提交订单 1,470 70% 30%
完成支付 882 60% 40%

整体转化率:882 / 10,000 = 8.82%


步骤 3: 流失原因诊断

针对流失率最高的步骤,分析原因:


步骤3.1: 识别关键流失节点

关键流失节点定义:流失率 > 30% 的步骤

示例

  • 步骤1→2:流失率70%(关键流失节点)
  • 步骤4→5:流失率40%(关键流失节点)

步骤3.2: 诊断流失原因

针对关键流失节点,使用 AskUserQuestion 询问:

步骤1→2(浏览详情页→加入购物车)流失率高达70%,可能的原因是?

A) 产品价格过高 B) 商品信息不清晰 C) 用户购买意愿不强 D) 竞品对比流失 E) 页面加载慢 F) 其他(请手动输入)

针对每个流失原因,引导用户深入分析:

请提供数据支撑或用户反馈(如有)


步骤3.3: 用户反馈收集

询问:

是否有用户调研或客服反馈数据?

A) 有用户调研数据 B) 有客服反馈记录 C) 有用户评论/投诉 D) 暂无数据,需要收集

如果选择D,提供数据收集建议:

建议收集方法

  1. 用户问卷调研(流失用户问卷)
  2. 客服反馈分析
  3. 用户访谈(深度访谈5-10人)
  4. 数据埋点(详细行为数据)

Read the full file on GitHub · 600 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 · 600 lines · 59 tokens per session scan A 2438ad79ba86

Subscribe to this mod's changes

pm-funnel is a skill published in the GitHub repository konglong87/superPM (62 stars, last pushed 4d ago), licensed MIT. It adds 59 tokens to every session and 4,224 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.

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