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icp-discoveryICP 发现

Agent Skill

icp-discovery 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

1,053

周安装

43

GitHub Stars

37

下载量

337
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

3

许可证

MIT

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:icp-discovery(ICP 发现)
来源仓库:https://github.com/majesticlabs-dev/majestic-marketplace
仓库路径:skills/icp-discovery
安装命令:
npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill icp-discovery
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill icp-discovery

简介

用于查找、检索和筛选与 ICP(目标客户画像)发现相关的资源。

  • 适合在市场分析中快速定位潜在客户特征和行为模式。
  • 需结合业务场景过滤噪声信息,聚焦高价值线索。icp-discovery 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 可通过 GitHub 仓库安装,支持多种 AI 宿主平台调用。
  • 使用前应确认来源数据是否经过验证,避免依赖未经验证的假设。

SKILL.md

ICP Discovery

Why ICP Matters

Everything downstream depends on ICP clarity:

  • Outbound: Who do you target?
  • Ads: What audiences do you build?
  • Content: Who are you writing for?
  • Sales calls: What pain points do you probe?
  • Pricing: What's their willingness to pay?
  • Product: What features matter most?

Bad ICP = wasted CAC, low conversion, high churn.

Conversation Starter

Use AskUserQuestion to gather initial context. Begin by asking:

"I'll help you discover and define your Ideal Customer Profile systematically.

Please provide:

  1. What you sell: Product/service, price point, contract length
  2. Current customers: Who are your best customers today? (Names, types, or descriptions)
  3. Worst customers: Who churned fastest or was most painful to serve?
  4. Sales cycle: How long? Who's involved in decisions?
  5. Current hypothesis: Who do you THINK your ICP is?
  6. Data available: Do you have access to customer data, CRM, or analytics?

I'll research your market and help you build a validated ICP framework."

Research Methodology

Use WebSearch extensively to find:

  • Industry benchmarks for their product category
  • Competitor positioning and target segments
  • Job postings that signal buying intent for their category
  • Community discussions (Reddit, LinkedIn) about their problem space
  • Technographic data patterns (what tools their ICP likely uses)

Required Deliverables

1. Current State Analysis

Analyze best vs. worst customers to find patterns:

  • Best customers: Industry, size, ACV, time to close, why they bought
  • Worst customers: Why they churned, warning signs
  • Hypothesis vs. reality gaps

Full template: assets/icp-templates.yaml

2. Firmographic Criteria

CriterionIdealAcceptableDisqualify
Employee count[Range][Range][Range]
Annual revenue[Range][Range][Range]
Industry[List][List][List]
Geography[Regions][Regions][Regions]

Plus: Technographic signals (CRM, marketing tools, engineering stack) and organizational signals (hiring patterns, funding, growth metrics).

3. Psychographic Criteria

  • Pain point intensity: Score 1-10 with urgency and frequency
  • Trigger events: What creates buying urgency (new exec, funding, competitor loss)
  • Buying behavior: Research style, decision speed, risk tolerance
  • Mindset & values: Growth orientation, tech adoption

Full template: assets/icp-templates.yaml

4. Buyer Personas (Within ICP)

PersonaKey Info
Economic BuyerGoals, fears, success metrics, objections
ChampionWhy they champion, how to enable them
UserDaily workflow, frustrations, adoption drivers
BlockerWhy they block, how to neutralize

Full persona templates: assets/icp-templates.yaml

5. Anti-ICP Definition

  • Hard disqualifiers: Signals that mean instant disqualify
  • Soft disqualifiers: Proceed with caution
  • Time-waster profiles: Tire kicker, feature demander, discount hunter, consensus seeker
  • Red flag questions: What prospects ask that signals bad fit

6. ICP Scoring Matrix

CriterionWeight3 (Ideal)2 (Good)1 (OK)0 (DQ)
Company sizeX%[Criteria][Criteria][Criteria][Criteria]
IndustryX%[Criteria][Criteria][Criteria][Criteria]
Pain intensityX%[Criteria][Criteria][Criteria][Criteria]
Commitment velocity10-15%3+ micro-yes/week1-2/week<1/weekGhosting

Score interpretation:

  • 85-100%: Tier 1 (prioritize)
  • 70-84%: Tier 2 (standard process)
  • 50-69%: Tier 3 (qualify harder)
  • <50%: Not ICP

7. ICP Segments (If Multiple)

For each segment:

  • Company size, industry, primary pain, buyer title
  • ACV and sales cycle
  • Go-to-market motion (PLG/Sales-led/Hybrid)
  • Prioritization based on TAM, win rate, LTV

8. Validation Methodology

  • Interview 5-10 best-fit customers
  • Validate each signal with data
  • Monitor for ICP drift
  • Quarterly review cadence

Full framework: assets/validation-activation.yaml

9. Activation Checklist

Update: Outbound targeting, ad audiences, lead scoring, website copy, sales playbook, content calendar, case studies, SDR training.

Full checklist: assets/validation-activation.yaml

Output Format

# ICP DISCOVERY: [Company Name]

## Executive Summary
[2-3 sentences: Who is your ICP and why]

## ICP One-Pager

**In one sentence:** We sell to [title] at [company type] who [pain point] and need to [outcome].

**Firmographics:**
- Size: [X-Y employees]
- Industry: [List]
- Geography: [Regions]

**Psychographics:**
- Primary pain: [Pain]
- Trigger: [Event]
- Buying style: [Description]

**Key Personas:**
- Buyer: [Title]
- Champion: [Title]
- User: [Title]

**Disqualifiers:**
- [Signal 1]
- [Signal 2]
- [Signal 3]

---

[Full sections using templates from assets/]

Quality Standards

  • Data-driven: Derive ICP from actual customer data, not assumptions
  • Specific enough to act on: Should be able to build a lead list from this
  • Broad enough to scale: Should represent a reachable market
  • Validated: Include methodology to test and refine

Tone

Strategic and analytical. Write like a revenue operations leader who has built ICP frameworks for multiple successful companies. Challenge assumptions, demand data, and push for specificity.

适合场景

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能力 5

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平台分布

Cursor

92.52%
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