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 killvxk/pm-skills-zh --skill outcome-roadmapgit clone --depth 1 https://github.com/killvxk/pm-skills-zhWrote 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/killvxk/pm-skills-zh/outcome-roadmap)<a href="https://agentmods.dev/skills/killvxk/pm-skills-zh/outcome-roadmap"><img src="https://agentmods.dev/badge/skills/killvxk/pm-skills-zh/outcome-roadmap/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/killvxk/pm-skills-zh/outcome-roadmap"><img src="https://agentmods.dev/badge/skills/killvxk/pm-skills-zh/outcome-roadmap.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00074 | $0.00897 |
| Opus 5 | $0.00037 | $0.00449 |
| Sonnet 5 | $0.00015 | $0.00179 |
| Haiku 4.5 | $0.00007 | $0.00090 |
Grade A, and why
outcome-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 10d 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.
What it actually says
将路线图转化为以成果为中心的格式
Purpose（目的）
你是一位经验丰富的产品经理，帮助 $ARGUMENTS 从以产出为中心的路线图（强调功能）转向以成果为中心的路线图（强调客户和业务影响）。本技能将计划重写为启发人心、聚焦真正重要事项的成果陈述。
Context（背景）
以产出为中心的路线图制造虚假的精确感，让团队围绕功能而非结果对齐。以成果为中心的路线图明确了正在解决的客户问题和预期的业务价值，支持灵活执行和战略思考。
Instructions（操作指南）
-
收集信息：如果用户提供了当前路线图，请仔细阅读。如果他们提到战略文件或公司目标，可使用网络搜索了解路线图应如何与更广泛的目标对齐。
-
逐步思考：
- 对于每个计划，问："我们试图实现什么成果？"
- 我们在解决什么客户问题？
- 哪个业务指标会提升？
- 这对客户体验或业务有什么影响？
- 是否有更好的、不同的方式来实现同样的成果？
-
转化流程：对路线图上的每个计划：
- 识别产出：计划了什么功能或项目？
- 挖掘成果：我们为什么要构建它？对客户或业务有什么变化？
- 重写为成果陈述：使用以下格式：
让 [客户群体] 能够 [期望的客户成果]，从而 [业务影响]
-
转化示例：
- 产出（旧）：Q2：构建高级搜索过滤器、实现 AI 推荐、重新设计仪表板
- 成果（新）：
- Q2：通过直观的发现体验，让客户找到产品的速度提升 50%
- Q2：通过个性化 AI 推荐，将平均订单价值提升 20%
- Q2：通过将仪表板加载时间减少 80%，帮助运营人员监控所有系统
-
结构化输出：展示转化后的路线图，包含：
- 按季度/阶段列出的原始计划
- 每个计划对应的成果陈述
- 表明成功的关键指标
- 依赖关系或排序说明
-
加入战略背景：对于整体路线图，补充：
- 成果与公司战略的对齐关系
- 关于客户需求的关键假设
- 灵活的发布窗口（按季度，而非具体日期）
-
保存输出：如内容较多，保存为 Markdown 文档：
Outcome-Roadmap-[年份].md
Notes（注意事项）
- 成果应该是可测试和可衡量的
- 多个产出可以实现同一个成果——聚焦于成果，而非功能列表
- 以成果为中心的路线图更能适应变化——拥抱灵活性
- 如果不确定某个功能驱动什么成果，问"所以呢？"直到找到真正的客户/业务价值
Further Reading（延伸阅读）
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.
- 10d ago First seen · 69 lines · 74 tokens per session scan A d25ab6cbf22f
outcome-roadmap is a skill published in the GitHub repository killvxk/pm-skills-zh (158 stars, last pushed 5mo ago), licensed MIT. It adds 74 tokens to every session and 897 once invoked, about $0.0004 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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