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.
npx skills add konglong87/superPM --skill pm-journeygit clone --depth 1 https://github.com/konglong87/superPMWrote 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.
[](https://agentmods.dev/skills/konglong87/superpm/pm-journey)<a href="https://agentmods.dev/skills/konglong87/superpm/pm-journey"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-journey/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/konglong87/superpm/pm-journey"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-journey.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00055 | $0.02638 |
| Opus 5 | $0.00028 | $0.01319 |
| Sonnet 5 | $0.00011 | $0.00528 |
| Haiku 4.5 | $0.00006 | $0.00264 |
Grade A, and why
pm-journey scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 411 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preamble (run first)
bash "$(dirname "${BASH_SOURCE[0]}")/../../check-update.sh" 2>/dev/null || true
# 创建需求调研目录
mkdir -p docs/01-需求调研
# 检查是否有需求调研报告
if [ ! -f "docs/01-需求调研/需求调研报告.md" ]; then
echo "⚠️ 未找到需求调研报告"
echo ""
echo "建议先执行 /pm-demand 了解用户信息"
echo ""
echo "您可以选择:"
echo "A) 执行 /pm-demand 先了解用户信息(推荐)"
echo "B) 手动输入用户信息(快速模式)"
fi
跨 Agent 交互规则
当流程要求与用户交互时:
- 如果当前环境支持 AskUserQuestion,使用 AskUserQuestion(最佳体验)。
- 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。
- 一次只问一个问题。
- 提问后必须停止当前回合,等待用户回答(STOP and WAIT)。
- 不得在用户回答前生成文档、写入 docs。
- 已有 docs 文件不能替代本轮用户回答。
执行流程
步骤 1: 读取前置数据
使用 Read 工具读取:
docs/01-需求调研/需求调研报告.md(提取目标用户)docs/01-需求调研/MVP方案.md(提取核心功能,如有)
步骤 2: 确定用户类型
使用 AskUserQuestion:
🎯 绘制哪类用户的旅程?
A) 新用户 - 首次使用产品的用户 B) 活跃用户 - 经常使用产品的用户 C) 流失用户 - 曾经活跃但已停止使用的用户 D) 付费用户 - 已付费的用户 E) 其他(请手动输入)
步骤 3: 确定旅程场景
用户要完成什么任务?
A) 核心任务 - 产品主要功能(如购买、下单) B) 入门任务 - 新用户引导流程 C) 探索任务 - 发现新功能 D) 问题解决 - 寻求帮助或解决问题 E) 其他(请手动输入)
步骤 4: 绘制用户旅程
AI 引导用户拆解旅程阶段:
问题 1: 旅程阶段
用户完成任务经历哪些阶段?
例如:"发现产品 → 注册 → 首次使用 → 深度使用 → 推荐分享"
请输入各个阶段(每行一个阶段):
用户输入后,记录到列表 JOURNEY_STAGES
问题 2: 每个阶段的详细分析
对每个阶段,AI 询问:
阶段: {阶段名称}
问题 2.1: 用户行为
在"{阶段名称}"阶段,用户具体做什么?
例如:"搜索关键词"、"浏览商品列表"、"对比价格"
请描述用户行为:
问题 2.2: 触点
用户通过什么渠道/入口进入这个阶段?
A) 移动APP B) 网页端 C) 小程序 D) 第三方平台 E) 其他(请手动输入)
问题 2.3: 用户情绪
在这个阶段,用户的情绪如何?
A) 期待兴奋 😊 B) 平静专注 😐 C) 困惑焦虑 😕 D) 挫败不满 😠 E) 满意愉悦 😄
记录到变量 USER_EMOTION
问题 2.4: 痛点
在这个阶段,用户可能遇到什么问题?
A) 操作复杂 - 步骤太多 B) 信息不清晰 - 不知道该做什么 C) 等待时间过长 D) 功能缺失 E) 无明显痛点
如果用户选择具体痛点,询问:
这个痛点有多严重?
A) 轻微 - 用户可以忍受 B) 中等 - 影响体验 C) 严重 - 可能导致用户流失
问题 2.5: 机会点
针对这个阶段的痛点,有什么改进机会?
请描述您的想法:
步骤 5: 绘制情绪曲线
AI 根据用户输入,绘制情绪曲线:
情绪值
5 | 😄
4 | 😊 😄
3 | 😐
2 | 😕
1 | 😠
0 +------------------------
发 注 首 深 推
现 册 次 度 荐
使 使 分
用 用 享
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.
- 9d ago First seen · 411 lines · 55 tokens per session scan A c4958d6945c7
pm-journey is a skill published in the GitHub repository konglong87/superPM (64 stars, last pushed 6d ago), licensed MIT. It adds 55 tokens to every session and 2,638 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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