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 agentmods add skills/konglong87/superpm/pm-roadmapnpx skills add konglong87/superPM --skill pm-roadmapgit 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-roadmap)<a href="https://agentmods.dev/skills/konglong87/superpm/pm-roadmap"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-roadmap.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00054 | $0.02401 |
| Opus 5 | $0.00027 | $0.01201 |
| Sonnet 5 | $0.00011 | $0.00480 |
| Haiku 4.5 | $0.00005 | $0.00240 |
Grade A, and why
pm-roadmap scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preamble
bash "$(dirname "${BASH_SOURCE[0]}")/../../check-update.sh" 2>/dev/null || true
mkdir -p docs/03-增长迭代
echo "🗺️ 产品路线图工具已启动"
# 检查前置文档
echo "📊 正在检查前置数据..."
if [ -f "docs/02-方案设计/PRD产品需求文档.md" ]; then
echo "✅ PRD文档 - 已找到"
else
echo "⏳ PRD文档 - 未找到"
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: 明确产品愿景与战略目标
使用 AskUserQuestion 询问:
🎯 产品愿景与战略目标
产品愿景:产品最终要成为什么? 示例:成为XX领域最受信赖的平台
时间范围:您想规划多长时间的路线图?
A) 3个月(近期规划) B) 6个月(中期规划) C) 12个月(年度规划) D) 2-3年(长期规划) E) 其他(请手动输入)
💡 提示:首次规划建议从6个月开始
记录到变量 VISION 和 TIMEFRAME
步骤 2: 设定核心目标
🎯 各阶段核心目标:
将{TIMEFRAME}划分为2-4个阶段,每个阶段设定一个核心目标。
示例(电商产品6个月路线图):
阶段 时间 核心目标 关键指标 阶段1 第1-2月 MVP上线验证 DAU达到1万 阶段2 第3-4月 用户增长 MAU达到10万 阶段3 第5-6月 商业变现 GMV达到100万 您希望如何划分阶段?
A) 根据功能主题划分(基础设施→核心功能→增长→变现) B) 根据用户规模划分(冷启动→增长→规模化) C) 根据商业目标划分(验证→获客→变现) D) 自定义划分(请手动输入)
步骤 3: 规划各阶段里程碑
对每个阶段,详细规划里程碑:
📅 阶段1详细规划
阶段名称:{阶段名称} 时间范围:{起止时间} 核心目标:{目标描述}
关键里程碑:
里程碑 时间 交付物 验收标准 M1 第X周 核心功能A上线 完成XX功能,达标XX指标 M2 第X周 核心功能B上线 完成XX功能,达标XX指标 M3 第X周 公测版本发布 完成全流程验证 关键指标目标:
- DAU目标:[X]万
- 转化率目标:[X]%
- NPS目标:[X]分
资源需求:
- 前端:[X]人
- 后端:[X]人
- 设计:[X]人
是否调整阶段1的规划?
A) 阶段1规划合理,继续阶段2 B) 需要调整里程碑 C) 需要调整资源分配
逐个阶段确认。
步骤 4: 识别关键依赖与风险
⚠️ 关键依赖与风险分析:
外部依赖:
- 第三方服务(支付、短信、地图等)
- 资质合规(牌照、备案等)
- 合作伙伴对接
内部依赖:
- 关键人员(核心开发、设计师)
- 技术基建(数据库、服务器)
- 数据基础设施
主要风险:
风险 概率 影响 应对措施 开发延期 高 里程碑延迟 预留20%缓冲时间 政策变化 中 产品方向调整 关注政策动态 竞品先发 中 市场空间压缩 快速验证,快速迭代 是否还有其他风险需要补充?
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.
- 5d ago First seen · 313 lines · 54 tokens per session scan A 0cfa68f5f1c1
pm-roadmap is a skill published in the GitHub repository konglong87/superPM (61 stars, last pushed yesterday), licensed MIT. It adds 54 tokens to every session and 2,401 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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