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.
git 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/commands/killvxk/pm-skills-zh/stakeholder-map)<a href="https://agentmods.dev/commands/killvxk/pm-skills-zh/stakeholder-map"><img src="https://agentmods.dev/badge/commands/killvxk/pm-skills-zh/stakeholder-map.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 5.1 | $0.00020 | $0.00988 |
| Opus 5 | $0.00010 | $0.00494 |
| Sonnet 5 | $0.00004 | $0.00198 |
| Haiku 4.5 | $0.00002 | $0.00099 |
Grade A, and why
stakeholder-map 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 7d 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
/stakeholder-map -- 干系人地图与沟通计划
识别项目的所有干系人，按影响力和关注度绘制地图，并生成沟通计划，确保合适的人在合适的时间获得合适的信息。
Invocation（调用示例）
/stakeholder-map 新分析平台上线
/stakeholder-map 影响所有客户的定价模式调整
/stakeholder-map [上传项目简报或组织架构图]
Workflow（工作流程）
Step 1：理解计划内容
询问：
- 项目或计划是什么？
- 当前处于哪个阶段？（规划中、开发中、发布中、发布后）
- 你已知的显性干系人有哪些？
- 是否有需要注意的政治敏感因素？
Step 2：识别干系人
集思广益，补充用户可能忽略的干系人：
- 内部：工程、设计、QA、数据、法务、财务、市场、销售、客户支持、高层领导
- 外部：客户、合作伙伴、供应商、监管机构、董事会成员
- 容易被忽略的：相邻团队、值班工程师、客户成功团队、文档团队
Step 3：映射到权力×利益方格
应用 stakeholder-map 技能：
将每位干系人放入对应象限：
高关注度
│
保持满意（Keep │ 重点管理（Manage
Satisfied） │ Closely）
高权力，低关注度 │ 高权力，高关注度
│
────────────────────┼────────────────────
│
持续监控（Monitor）│ 及时告知（Keep
低权力，低关注度 │ Informed）
│ 低权力，高关注度
低关注度
Step 4：生成沟通计划
## 干系人地图：[计划名称]
### 干系人方格
| 干系人 | 角色 | 权力 | 关注度 | 象限 | 立场 |
|-------|------|------|-------|------|------|
### 沟通计划
#### 重点管理（高权力，高关注度）
| 干系人 | 渠道 | 频率 | 内容 | 负责人 |
|-------|------|------|------|-------|
#### 保持满意（高权力，低关注度）
| 干系人 | 渠道 | 频率 | 内容 | 负责人 |
|-------|------|------|------|-------|
#### 及时告知（低权力，高关注度）
| 干系人 | 渠道 | 频率 | 内容 | 负责人 |
|-------|------|------|------|-------|
#### 持续监控（低权力，低关注度）
[轻量化沟通——仅纳入广泛更新即可]
### 潜在冲突
[干系人利益可能存在分歧的地方——附对齐策略]
### 升级路径
[决策受阻时应向谁寻求支持]
### RACI 矩阵
| 决策领域 | 执行（R） | 负责（A） | 咨询（C） | 知会（I） |
|---------|---------|---------|---------|---------|
保存为 Markdown 格式。
Step 5：提供后续建议
- "需要我为"重点管理"组起草第一份干系人更新通知吗？"
- "需要我为关键干系人对话创建会前准备简报吗？"
- "需要我将沟通节奏设置为周期性检查清单吗？"
Notes（注意事项）
- "重点管理"象限是 PM 投入最多政治资本的地方——把这些关系处理好
- "立场"（支持、中立、抵触）有助于判断在哪里优先投入关系建设精力
- 不要忽视下游干系人：支持、文档和销售赋能团队经常在发布时才被告知
- 随着项目推进持续更新地图——干系人的关注度会随项目阶段而变化
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.
- 7d ago First seen · 107 lines · 20 tokens per session scan A 98e8957758bb
stakeholder-map is a command published in the GitHub repository killvxk/pm-skills-zh (151 stars, last pushed 5mo ago), licensed MIT. It adds 20 tokens to every session and 988 once invoked, about $0.0001 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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