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Agent Skill · 研究检索

customer-intel(客户情报)

customer-intel 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。

customer-intel 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 59,000。

总安装 396周安装 17GitHub Stars 55下载 139核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:customer-intel(客户情报)
来源仓库:https://github.com/vm0-ai/vm0-skills
仓库路径:skills/customer-intel
安装命令:
npx skills add https://github.com/vm0-ai/vm0-skills --skill customer-intel
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/vm0-ai/vm0-skills --skill customer-intel

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

customer-intel 系统性地调查客户背景与体验,输出结构化情报摘要。适用于需要事实核查、上下文还原或开放式探索的客户相关问题分析。采用三阶段调查框架:定义问题类型、选择受众视角、组织证据链。结果受网络搜索限制,无法保证全面覆盖或精确成员数统计。

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。

来源仓库内路径:skills/customer-intel

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/vm0-ai/vm0-skills --skill customer-intel;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

customer-intel 怎么安装?

在终端执行 npx skills add https://github.com/vm0-ai/vm0-skills --skill customer-intel。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

customer-intel 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

customer-intel 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

customer-intel 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

customer-intel 用的人多吗?

公开数据是累计安装 396 次,近一周安装 17 次,下载 139 次,GitHub 55 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

customer-intel 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
customer-intel

客户情报 · 本页

39655需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Investigation Framework

Phase 1 — Define the Inquiry

Before touching any source, characterize what you need to find:

  • Definitive fact: A single correct answer exists (e.g., "Does the API support batch requests?")
  • Contextual picture: Multiple viewpoints must be assembled (e.g., "What has this account's experience been over the last quarter?")
  • Open exploration: The boundaries of the question are still forming (e.g., "Why are enterprise customers struggling with onboarding?")
  • Audience awareness: Determine who will consume the answer — the customer directly, an internal team member, or executive leadership — as this shapes tone, depth, and what to include.

Phase 2 — Map Sources to the Question Type

Question CategoryPrimary Sources
Product capabilitiesOfficial docs, API references, knowledge base, product specs
Account history and contextCRM records, email threads, meeting notes, chat logs
Internal process or policyWikis, runbooks, policy documents
Technical troubleshootingDocumentation, engineering resources, past support tickets
Market or competitive landscapeWeb search, analyst reports, competitive intelligence

Phase 3 — Gather Evidence Across Tiers

Work through sources from most to least authoritative. Never rely on a single hit — corroborate across channels.

Tier 1: Canonical Internal Records (Reliability: Strong) Official documentation, published knowledge base articles, API references, policy and SLA documents, internal product roadmaps. Trust these unless they carry stale dates.

Tier 2: Organizational Memory (Reliability: Moderate-Strong) CRM account notes and activity logs, resolved support tickets and known-issue databases, shared documents and specifications, recorded decisions from meeting notes.

Tier 3: Informal Team Channels (Reliability: Moderate) Slack or chat discussions, email correspondence, calendar and agenda notes. These often hold the freshest information but may lack full context or reflect speculation.

Tier 4: Public and External Sources (Reliability: Variable) Company and competitor websites, community forums and user discussions, partner documentation, industry news and analyst commentary.

Tier 5: Reasoning by Analogy (Reliability: Weak) Precedent from similar past situations, patterns from comparable accounts, general industry conventions. Always label these as inference.

Phase 4 — Assemble the Answer

Pull together findings, flag any contradictions between sources, and assign an overall confidence rating.

Phase 5 — Attribute Everything

Every claim in your response must trace back to a named source. No unsourced assertions.

Confidence Rating System

Attach one of these ratings to every answer you deliver:

Strong Confidence

  • Backed by canonical documentation or an authoritative internal record
  • Corroborated by at least two independent sources
  • Verified as current
  • Phrasing: "This is well-supported by [source]."

Moderate Confidence

  • Found in informal channels (chat, email) without official documentation backing
  • Rests on a single uncorroborated source
  • Possibly dated but likely still accurate
  • Phrasing: "According to [source], this seems correct. I would suggest confirming with [team/person]."

Weak Confidence

  • Derived from indirect or analogical reasoning
  • Sources are old or of uncertain reliability
  • Multiple sources conflict with one another
  • Phrasing: "No definitive source was found. Based on [context], my working assessment is [answer]. Verification is recommended before communicating to the customer."

Insufficient Information

  • No relevant material located anywhere
  • The question demands expertise beyond what available sources cover
  • Phrasing: "I was unable to locate relevant information. I recommend consulting [suggested expert or team]."

Resolving Source Conflicts

When different sources tell different stories:

  1. Surface the discrepancy explicitly — never silently pick one version
  2. Evaluate recency and authority of each conflicting source
  3. Lay out both positions with context for the reader
  4. Propose a path to resolution (e.g., check with the product team)
  5. For customer-facing answers, default to the most conservative position until the conflict is settled

Structured Response Format

**Answer:** [Lead with the bottom line]

**Confidence:** [Strong / Moderate / Weak]

**Evidence:**
- [Source A]: [What it states]
- [Source B]: [Corroborating or contrasting detail]

**Limitations:**
- [Conditions or edge cases that could change the answer]
- [Context-specific factors to be aware of]

**Next Steps:**
- [Whether this is safe to relay to the customer as-is]
- [Any recommended verification actions]

Deciding When to Escalate

Safe to Answer Directly

  • Official docs address the question unambiguously
  • Multiple trustworthy sources agree
  • The topic is factual and non-sensitive
  • No commitments about timelines, pricing, or legal terms are involved

Route to a Specialist

  • Roadmap commitments or delivery timelines are in play
  • The question touches pricing, contracts, or legal terms
  • Security, compliance, or data-handling topics
  • The response could set a binding precedent or create expectations
  • Conflicting information was found and remains unresolved
  • A customer-specific configuration is involved
  • The account is at risk and an incorrect answer could worsen the situation

Escalation Directory

  1. Domain experts — technical or specialized knowledge gaps
  2. Product team — capability, roadmap, or feature questions
  3. Legal / compliance — regulatory, privacy, or contractual matters
  4. Finance / billing — pricing, invoicing, payment issues
  5. Engineering — bugs, custom setups, root-cause analysis
  6. Leadership — strategic decisions, policy exceptions, high-stakes situations

Capturing Research for Reuse

Worth Documenting When:

  • The same question has surfaced before or is likely to recur
  • The investigation required substantial effort
  • The answer corrects a widespread misconception
  • Nuance exists that is easy to get wrong

Reusable Entry Format

## [Topic or Question]

**Verified On:** [date]
**Confidence:** [rating]

### Finding
[Concise, direct answer]

### Context and Nuance
[Background, conditions, and subtleties]

### Source Trail
[Where this information originated]

### Adjacent Topics
[Related questions this entry may also answer]

### Freshness Notes
[When to re-check, what developments could invalidate this]

Maintaining the Knowledge Store

  • Timestamp every entry
  • Mark entries tied to specific product versions or feature states
  • Schedule periodic reviews to retire stale content
  • Tag entries by domain, product area, and customer segment for discoverability

Operating Principles

  1. Pin down exactly what you are looking for before searching
  2. Work through source tiers methodically — do not skip levels on assumption
  3. Corroborate across multiple channels whenever possible
  4. Never present uncertain findings as established fact — always surface your confidence level
  5. When unsure whether an answer is safe to share externally, verify first
  6. Record your findings so the next person does not repeat the work
  7. If your research uncovers a knowledge gap, flag it for documentation

平台分布

Codex

36.46%
按下载量换算51

Claude

29.59%
按下载量换算41

Cursor

19.44%
按下载量换算27

Gemini CLI

9.41%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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