beachhead-segment

beachhead-segment is a skill for Claude Code from killvxk/pm-skills-zh. It costs 72 tokens per session (1,651 once invoked), scanned A, original, MIT.

A market-selection skill for choosing the first customer group to target when launching a product. This first target is called a beachhead segment because it provides an initial foothold for later expansion.

In plain words
What is it for?
Selecting early adopters, prioritizing an initial market, testing product-market fit, evaluating market attractiveness, and planning an initial go-to-market focus.
Why use it?
It compares customer groups using the urgency of their problem, willingness to pay, competitive conditions, and likelihood of referrals. This helps teams focus limited launch resources.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution.

Part of the pm-go-to-market plugin — 6 skills, 3 commands shipped together

Good fit Selecting early adopters, prioritizing an initial market, testing product-market fit, evaluating market attractiveness, and planning an initial go-to-market focus.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/killvxk/pm-skills-zh/beachhead-segment
Install

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.

Any agent
npx skills add killvxk/pm-skills-zh --skill beachhead-segment
Clone the repo
git clone --depth 1 https://github.com/killvxk/pm-skills-zh

Made for: Claude Code.

Or install pm-go-to-market, the plugin that ships this one along with the rest of its 6 skills, 3 commands.

Wrote 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.

agentmods badge for beachhead-segment

README.md
[![agentmods](https://agentmods.dev/badge/skills/killvxk/pm-skills-zh/beachhead-segment/github.svg)](https://agentmods.dev/skills/killvxk/pm-skills-zh/beachhead-segment)
Your own site
<a href="https://agentmods.dev/skills/killvxk/pm-skills-zh/beachhead-segment"><img src="https://agentmods.dev/badge/skills/killvxk/pm-skills-zh/beachhead-segment/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.

agentmods 80×15 button for beachhead-segment

Your own site · 80×15
<a href="https://agentmods.dev/skills/killvxk/pm-skills-zh/beachhead-segment"><img src="https://agentmods.dev/badge/skills/killvxk/pm-skills-zh/beachhead-segment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,651 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.01651
Opus 5 $0.00036 $0.00826
Sonnet 5 $0.00014 $0.00330
Haiku 4.5 $0.00007 $0.00165

Measured 9d ago against content hash 58f99b1903d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

beachhead-segment 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.

pm-go-to-market/skills/beachhead-segment/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

桥头堡细分市场

概述

为产品上市确定第一个桥头堡细分市场。本技能根据关键标准评估潜在市场细分,找到能够快速验证 PMF(产品市场契合度)并支撑后续扩张的初始胜出细分市场。

适用场景

  • 为产品选择初始市场
  • 锁定最早期的目标客户群体
  • 规划初始市场进入策略
  • 决定如何集中有限的资源
  • 通过早期采用者验证 GTM 假设

核心评估标准

1. 痛点强烈程度

该细分市场是否存在迫切的、尚未被满足的痛点?

  • 对现状的日常性不满
  • 显著的生产力损失或成本影响
  • 强烈的找解决方案的主观意愿
  • 现有替代方案代价高昂或不够稳定
  • 问题随时间推移愈发严重

2. 付费意愿

该细分市场是否有预算和动力为解决方案付费?

  • 已记录在案的该问题领域预算投入
  • ROI(投资回报率)清晰且令人信服(价值 > 成本)
  • 问题带来的经济影响足以支撑解决方案的成本
  • 决策者对预算有自主权或影响力
  • 没有能完全满足需求的免费或自建替代方案

3. 市场可赢性

你能否在 3 到 18 个月内现实地拿下该细分市场 60-70% 的份额?

  • 市场规模足够大,但竞争尚未饱和
  • 竞争有限或差异化容易实现
  • 现有市场参与者分散或反应迟钝
  • 你的产品具有明确的竞争优势
  • 你在触达或分发上有独特的渠道优势

4. 转介绍潜力

客户是否会自然地转介绍或推荐给他人?

  • 该细分市场存在职业社群
  • 客户与相邻细分市场有交集(扩张机会)
  • 所在行业有强烈的口碑文化
  • 细分市场内部存在网络效应
  • 为一个客群解决问题,会在相邻客群中创造需求

工作方式

第一步:列出潜在细分市场

对所有可能的目标细分市场进行头脑风暴:

  • 行业垂直(SaaS、医疗、制造业等)
  • 公司规模(中小企业、中端市场、企业客户)
  • 职位或角色
  • 地理区域
  • 使用场景或使用场景变体
  • 客户成熟度水平

第二步:调研痛点

验证各细分市场的痛点强烈程度:

  • 客户访谈和调研通话
  • 通过问卷进行问题验证
  • 市场调研和分析师报告
  • 竞争对手的定位和客户评价
  • 量化问题的成本/影响
  • 识别现有替代方案及其局限性

第三步:评估付费意愿

确定预算和经济可行性:

  • 该细分市场在此问题类别上的预算
  • ROI 计算(获得的价值 vs 成本)
  • 当前在解决方案或替代方案上的支出
  • 预算决策流程
  • 典型的预期成交规模
  • 该细分市场对价格的敏感度

第四步:评估可赢性

评估现实的市场份额潜力:

  • 总潜在市场(TAM)规模
  • 竞争格局和产品定位
  • 你的差异化点或不对称优势
  • 触达该细分市场的渠道通路
  • 所需时间和资源
  • 市场增长趋势和势能

第五步:识别转介绍路径

梳理扩张机会:

  • 目标细分市场能影响到的相邻细分市场
  • 细分市场内部的网络效应
  • 职业社群和行业协会
  • 客户间的相互推荐
  • 向相邻市场自然扩张的路径
  • 解决核心痛点所产生的病毒或网络效应

第六步:选定桥头堡

选择主要上市细分市场:

  • 在四项标准上综合得分最高
  • 以现有资源最具可行性
  • 到达 PMF(产品市场契合度)和产生营收的路径最短
  • 对相邻扩张最具参考价值
  • 早期客户群体热情最高

输入格式

通过 $ARGUMENTS 传入:

  • 产品描述和核心能力
  • 初步市场调研和验证数据
  • 候选细分市场选项
  • 约束条件和局限性
  • 时间线和资源限制
  • 现有客户数据或反馈

输出内容

包含以下内容的桥头堡细分市场分析报告:

  • 3-5 个推荐细分市场及评分
  • 主要桥头堡细分市场建议
  • 痛点验证及证据
  • 付费意愿评估及定价指导
  • 现实的市场份额和营收预测
  • 向相邻细分市场的转介绍和扩张路径
  • 桥头堡 90 天客户获取计划
  • 桥头堡之后的扩张路线图

方法论

基于 Geoffrey Moore《跨越鸿沟》中的桥头堡市场策略。聚焦于找到规模最小、最容易赢得且可作为参考案例的市场,从而验证 PMF 并支撑后续扩张。

实用技巧

  • 从极度具体的细分开始。一个小众的桥头堡胜过模糊的大众市场
  • 选择最有可能成为你产品布道者的细分市场
  • 通过至少 10 次客户访谈验证四项标准
  • 选择能最快实现营收和客户案例的细分市场
  • 确保桥头堡客户能向相邻细分市场进行推荐
  • 将全部资源集中在拿下桥头堡(而非分散精力)
  • 只有在桥头堡市场份额达到 60% 以上后,才考虑向外扩张

延伸阅读

Read the full file on GitHub · 146 lines

Changes

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.

  1. 9d ago First seen · 146 lines · 72 tokens per session scan A 58f99b1903d3

Subscribe to this mod's changes

beachhead-segment is a skill published in the GitHub repository killvxk/pm-skills-zh (156 stars, last pushed 5mo ago), licensed MIT. It adds 72 tokens to every session and 1,651 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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