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opportunity-mapping机会图

Agent Skill

opportunity-mapping 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

456

周安装

19

GitHub Stars

33

下载量

152
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:opportunity-mapping(机会图)
来源仓库:https://github.com/assimovt/productskills
仓库路径:skills/opportunity-mapping
安装命令:
npx skills add https://github.com/assimovt/productskills --skill opportunity-mapping
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/assimovt/productskills --skill opportunity-mapping

简介

该技能用于查找和筛选机会映射相关的信息和资源。

  • 适用于市场分析、产品定位和竞争策略制定。
  • 通过关键词搜索获取机会识别和评估方法。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。
  • 建议结合具体业务场景验证机会的可行性。
  • opportunity-mapping 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Map opportunities by connecting business outcomes to customer needs to testable solutions. Teresa Torres' Opportunity Solution Trees (OSTs) prevent the two biggest PM mistakes: building solutions without clear problems, and chasing problems disconnected from business goals.

Opportunity Solution Tree Structure

Build the tree top-down, but fill it bottom-up with evidence:

Desired Outcome (business metric you're trying to move)
  |
  +-- Opportunity 1 (customer need/pain/desire)
  |     +-- Solution A
  |     |     +-- Experiment 1
  |     |     +-- Experiment 2
  |     +-- Solution B
  |           +-- Experiment 3
  |
  +-- Opportunity 2
        +-- Solution C
        +-- Solution D
              +-- Experiment 4

Level 1: Desired Outcome

One measurable business outcome. Not a feature, not a project — a metric.

  • "Increase 7-day activation rate from 23% to 40%"
  • NOT: "Improve onboarding" (not measurable)

Level 2: Opportunities

Customer needs, pain points, or desires that, if addressed, would move the outcome. These come from research — interviews, data, support tickets — not brainstorming.

Rules for good opportunities:

  • Framed as customer needs, not product features
  • "New users don't understand what to do first" (opportunity)
  • NOT "Add an onboarding wizard" (solution masquerading as opportunity)
  • Each opportunity is independent — addressing one doesn't depend on another

Level 3: Solutions

Multiple possible solutions for each opportunity. Generate at least 3 before evaluating. The goal is to explore the solution space, not commit to the first idea.

Level 4: Experiments

Small, fast tests to validate whether a solution addresses the opportunity. Experiments should answer: "Does this solution actually solve this opportunity?"

Building the Tree

  1. Start with the outcome. Align with your team or stakeholders on exactly one outcome to focus on.
  2. Map opportunities from research. Review interview notes, support tickets, analytics. Cluster evidence into distinct opportunities. Each opportunity needs evidence from 3+ sources.
  3. Generate solutions per opportunity. Brainstorm at least 3 solutions per opportunity. Include wild ideas — they often reveal assumptions.
  4. Design experiments per solution. What's the smallest test? Prototype, concierge, Wizard of Oz, fake door, A/B test.
  5. Prioritize which branch to explore. You can't test everything. Pick the opportunity with strongest evidence and the solution with lowest experiment cost.

Guidelines

  • CRITICAL: NEVER skip from outcome directly to solutions. The opportunity layer is where the insight lives.
  • ALWAYS frame opportunities as customer needs, not features. If it sounds like a feature, push back to the underlying need.
  • NEVER have only one solution per opportunity. If you can't think of 3 solutions, you haven't explored the space.
  • ALWAYS ground opportunities in evidence from research, not assumptions.
  • NEVER pursue more than 2-3 opportunities simultaneously. Focus beats breadth.
  • ALWAYS design experiments that could DISPROVE your solution, not just confirm it.

*Built on Continuous Discovery Habits by Teresa Torres. Skills from productskills.*

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.38%
按下载量换算51

Claude

33.39%
按下载量换算51

Cursor

19.72%
按下载量换算30

Gemini CLI

10.59%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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