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 commands/killvxk/pm-skills-zh/plan-launchgit 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/plan-launch)<a href="https://agentmods.dev/commands/killvxk/pm-skills-zh/plan-launch"><img src="https://agentmods.dev/badge/commands/killvxk/pm-skills-zh/plan-launch.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 | $0.00029 | $0.01309 |
| Opus 5 | $0.00015 | $0.00655 |
| Sonnet 5 | $0.00006 | $0.00262 |
| Haiku 4.5 | $0.00003 | $0.00131 |
Grade A, and why
plan-launch 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 — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/plan-launch -- 市场进入策略
从零开始构建完整的 GTM（市场进入策略）方案：识别桥头堡市场、定义理想客户、提炼核心信息、选择渠道，并制定上市时间表。
调用方式
/plan-launch 面向咨询公司的 AI 驱动提案撰写工具
/plan-launch 项目管理工具的新企业版套餐
/plan-launch [上传 PRD、战略文档或 Pitch Deck]
工作流程
第一步：了解上市背景
询问以下问题：
- 你要上市的是什么？（新产品、新功能、新套餐、市场扩张）
- 当前处于什么阶段？（上市前规划、即将上线、上市后优化）
- 你已有现有客户，还是从零开始？
- 时间线是什么？有没有硬性截止日期？
- 预算限制？团队规模？
第二步：确定桥头堡细分市场
调用 beachhead-segment 技能：
- 根据以下标准评估潜在市场细分：
- 痛点强烈程度（他们有多迫切需要这个产品）
- 付费意愿（预算和采购决策权）
- 市场可赢性（能否触达并拿下该客群）
- 转介绍潜力（他们是否会向他人推荐）
- 给出最佳切入细分市场的建议及理由
- 规划桥头堡站稳后可向哪些相邻细分市场扩展
第三步：定义理想客户画像（ICP）
调用 ideal-customer-profile 技能：
- 人口特征：公司规模、行业、地域、技术栈
- 行为特征：如何发现解决方案、采购流程、决策人
- JTBD（用户待办任务）：他们雇用你的产品来完成的具体任务
- 现有替代方案：他们当前使用什么，以及为何不够用
- 资格甄别标准：如何快速识别目标客户
第四步：构建 GTM 策略
调用 gtm-strategy 技能：
- 产品定位：如何向该细分市场描述你自己
- 核心信息：面向不同利益相关方的关键信息（买家、用户、影响者）
- 渠道选择：在哪里、如何触达你的 ICP（按预期 ROI 排序）
- 上市战术：上市前、上市当天和上市后的具体行动
- 定价协同：定价如何支撑 GTM 打法
- 成功指标：如何判断上市是否成功
第五步：生成 GTM 方案
## 市场进入方案：[产品/功能名称]
**上市日期**：[目标日期]
**类型**：[新产品 / 新功能 / 新套餐 / 市场扩张]
### 桥头堡细分市场
**目标客群**：[具体的细分市场定义]
**为何优先选择他们**：[基于评估标准的理由]
**市场规模**：[TAM/SAM/SOM 估算]
### 理想客户画像（ICP）
| 属性 | 定义 |
|------|------|
| 公司规模 | [范围] |
| 行业 | [具体行业] |
| 决策者 | [职位/角色] |
| 核心 JTBD | [需要完成的任务] |
| 当前方案 | [他们目前使用的产品] |
| 识别信号 | [如何快速识别目标客户] |
### 产品定位与核心信息
**定位陈述**：对于 [目标客群]，他们 [需求]，[产品名] 是 [品类] 中能够 [核心价值] 的解决方案。与 [替代方案] 不同，我们 [差异化点]。
**面向各利益相关方的核心信息**：
| 受众 | 核心信息 | 佐证材料 |
|------|---------|---------|
### 渠道策略
| 渠道 | 战术 | 覆盖范围 | 成本 | 优先级 |
|------|------|---------|------|-------|
### 上市时间线
| 阶段 | 时间 | 行动 | 负责人 |
|------|------|------|-------|
| 上市前 | [日期] | [清单] | [负责人] |
| 上市周 | [日期] | [清单] | [负责人] |
| 上市后 | [日期] | [清单] | [负责人] |
### 成功指标
| 指标 | 30 天目标 | 90 天目标 |
|------|---------|---------|
### 风险与应对
| 风险 | 可能性 | 影响 | 应对措施 |
|------|-------|------|---------|
### 扩张计划
[桥头堡站稳后：按什么顺序进入哪些相邻细分市场，需要做哪些调整]
保存为 Markdown 格式。
第六步：提供后续建议
- "需要我为上市后的持续增长设计增长循环吗？"
- "要不要为销售团队制作竞争作战卡？"
- "需要我为上市撰写营销文案吗？"
- "要不要搭建上市跟踪指标看板？"
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 · 131 lines · 29 tokens per session scan A d11f2f971e6f
plan-launch is a command published in the GitHub repository killvxk/pm-skills-zh (151 stars, last pushed 5mo ago), licensed MIT. It adds 29 tokens to every session and 1,309 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.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.