pm-position

pm-position is a skill for Claude Code, Codex from konglong87/superPM. It costs 46 tokens per session (2,265 once invoked), scanned A, original, MIT.

A guided process for defining a product’s market position, value, audience, competitive difference, business model, pricing, and revenue plan. The instructions are written mainly in Chinese.

In plain words
What is it for?
Use it to clarify target markets, choose a market entry angle, shape a value proposition, identify differentiation, and plan pricing or monetization.
Why use it?
It structures product-strategy work and requires user input at key decisions before documents are written. The input does not describe any automated analysis or data source.

Skill for Claude CodeCodex

Part of the superPM plugin — 55 skills, 1 hook shipped together

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.

agentmods
npx agentmods add skills/konglong87/superpm/pm-position
Any agent
npx skills add konglong87/superPM --skill pm-position
Clone the repo
git clone --depth 1 https://github.com/konglong87/superPM

Made for: Claude Code, Codex.

Or install superPM, the plugin that ships this one along with the rest of its 55 skills, 1 hook.

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 pm-position

README.md
[![agentmods](https://agentmods.dev/badge/skills/konglong87/superpm/pm-position.svg)](https://agentmods.dev/skills/konglong87/superpm/pm-position)
Your own site
<a href="https://agentmods.dev/skills/konglong87/superpm/pm-position"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-position.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,265 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00046 $0.02265
Opus 5 $0.00023 $0.01132
Sonnet 5 $0.00009 $0.00453
Haiku 4.5 $0.00005 $0.00227

Measured 5d ago against content hash 185947a9daa6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pm-position 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.

skills/02-solution-design/pm-position/SKILL.md · 264 lines

How it starts

The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Preamble (run first)

bash "$(dirname "${BASH_SOURCE[0]}")/../../check-update.sh" 2>/dev/null || true
mkdir -p docs/02-方案设计

echo "📊 正在检查前置文档..."
if [ -f "docs/01-需求调研/需求调研报告.md" ]; then
  echo "✅ 需求调研报告 - 已找到"
else
  echo "⏳ 需求调研报告 - 未找到"
fi
if [ -f "docs/01-需求调研/市场调研报告.md" ]; then
  echo "✅ 市场调研报告 - 已找到"
else
  echo "⏳ 市场调研报告 - 未找到"
fi

跨 Agent 交互规则

当流程要求与用户交互时:

  1. 如果当前环境支持 AskUserQuestion,使用 AskUserQuestion(最佳体验)。
  2. 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。
  3. 一次只问一个问题。
  4. 提问后必须停止当前回合,等待用户回答(STOP and WAIT)。
  5. 不得在用户回答前生成文档、写入 docs。
  6. 已有 docs 文件不能替代本轮用户回答。

执行流程

步骤 1: 明确产品定位

您希望通过产品定位解决什么问题?

A) 明确产品在市场中的位置(市场定位) B) 明确产品的核心价值主张(价值定位) C) 明确目标用户和场景(用户定位) D) 明确与竞品的差异(竞争定位) E) 全方位产品定位(包含以上所有)


步骤 2: 市场定位

2.1 目标市场分析

🎯 目标市场分析:

市场规模:TAM(总市场){数据} / SAM(可服务){数据} / SOM(可获取){数据} 市场增长:年增长率{数据},驱动因素{因素}

您希望聚焦哪个细分市场?

A) 大众市场(覆盖广泛) B) 细分市场(聚焦特定人群) C) 垂直市场(深耕垂直领域)

2.2 市场切入点

切入点选择: A) 痛点切入 - 需求明确,竞争激烈 B) 技术创新切入 - 差异化明显,技术壁垒 C) 模式创新切入 - 先发优势,可复制 D) 价格优势切入 - 价格敏感用户,利润率低


步骤 3: 价值定位

3.1 核心价值主张

💎 价值主张模板: "为{目标用户},提供{核心价值},相比{竞品},我们{差异化优势}"

例:"为25-35岁白领,提供30分钟生鲜配送,相比传统电商,我们通过前置仓实现极速配送"

请补充您的价值主张,A) 符合继续 B) 需要调整

3.2 差异化优势

⭐ 差异化维度(选2-3个核心): A) 产品功能 B) 用户体验 C) 价格 D) 服务 E) 品牌 F) 技术


步骤 4: 用户定位

4.1 目标用户画像

👥 细化用户画像:

  • 人口统计:年龄、性别、地域、收入、职业
  • 心理特征:价值观、生活方式、消费习惯
  • 行为特征:使用场景、频率、痛点
4.2 用户使用场景

🎬 典型使用场景: 场景N:{用户}在{触发}时想达成{目标},现有方案不足{痛点},你的产品提供{价值}


步骤 5: 竞争定位

5.1 竞品分析(Subagent 并行优化)

使用 AskUserQuestion 收集竞品列表:

请列出您的主要竞品(建议2-5个):

用户输入后,记录到变量 COMPETITOR_LIST

并行派发 subagent 分析每个竞品

使用 Agent 工具并行派发 N 个 subagent(N = 竞品数量):

Agent 1: 分析竞品1 - prompt 包含竞品名称和分析维度(定位/用户/功能/优劣势/市场表现),输出JSON
Agent 2: 分析竞品2 - [同上结构]
Agent N: 分析竞品N - [同上结构]

主 agent 等待所有 subagent 完成,收集结果生成对比表格:

维度 竞品1 竞品2 竞品3 我们
定位 ... ... ... ...
目标用户 ... ... ... ...
优势 ... ... ... ...
劣势 ... ... ... ...

Read the full file on GitHub · 264 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 5d ago First seen · 264 lines · 46 tokens per session scan A 185947a9daa6

Subscribe to this mod's changes

pm-position is a skill published in the GitHub repository konglong87/superPM (60 stars, last pushed 22d ago), licensed MIT. It adds 46 tokens to every session and 2,265 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

deepsafe-scan

Preflight security scanner for AI coding agents — scans deployment config, skills/MCP servers, memory/sessions, and AI agent config files (hooks injection) for secrets, PII, prompt injection, and dangerous patterns. Runs 4 model behavior probes (persuasion, sandbagging, deception, hallucination). Supports LLM-enhanced…

XiaoYiWeio/deepsafe-scan · 120 tokens

douyin-upload-mcp-skill

通过抖音创作者平台(creator.douyin.com)发布视频和图文内容。首选调用 MCP 工具完成操作,MCP 无法满足时可运行 Skill 脚本兜底。禁止自行启动外部浏览器访问抖音。.

WJZ-P/douyin-upload-mcp-skill · 67 tokens

team-tasks

Coordinate multi-agent development pipelines using shared JSON task files. Use when dispatching work across dev team agents (code-agent, test-agent, docs-agent, monitor-bot), tracking pipeline progress, or running sequential/parallel workflows. Covers project init, task assignment, status tracking, agent dispatch via…

win4r/team-tasks · 88 tokens

multi-search

智能多引擎搜索,自动检测网络环境并按优先级切换:DuckDuckGo -> Tavily -> Bing API -> Bing爬虫。支持自动配额管理和网络缓存。Invoke when user needs web search with automatic engine selection and network adaptation.

Nex-ZMH/Agent-websearch-skill · 60 tokens

daily-standup-journal

Generate concise daily standups, reflection prompts, and weekly retrospectives for individuals or teams. Use for planning a day, surfacing blockers, reviewing user-provided entries, or drafting a check-in without assuming prior history.

iflytek/skillhub · 51 tokens

study-strategy-selector

Recommend practical study strategies matched to the material, learning goal, assessment, time, and learner constraints. Use for revision planning, homework routines, independent study, replacing ineffective habits, or adapting recall, spacing, explanation, and practice activities.

iflytek/skillhub · 52 tokens