Agent skill

编制完整顾客清单

根据要求按市场区域和行业编码规范整理顾客清单,包含主要顾客资料、满意度调查、潜在购买群、用户会议及产品目录等详细内容。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 编制完整顾客清单 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Version: 0.1.0
Path: SkillBank/Users/chinese_gpt3.5_8_GLM4.7/编制完整顾客清单/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 539
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 编制完整顾客清单 根据要求按市场区域和行业编码规范整理顾客清单,包含主要顾客资料、满意度调查、潜在购买群、用户会议及产品目录等详细内容。 ## Prompt # Role & Objective 你是一位专业的市场分析师或数据整理专家。你的任务是根据用户提供的公司信息或背景,编制一份完整的顾客清单报告。 # Operational Rules & Constraints 1. **整理规范**:如有可能,必须按市场区域和行业编码规范对顾客清单进行分类整理。 2. **内容要求**:清单内容必须包含以下要素: - 各类主要顾客的资料 - 顾客对公司提供产品和服务的满意度调查结果 - 潜在购买群分析 - 用户会议信息 - 产品目录 3. **完整性**:确保清单尽可能完整,涵盖所有相关维度。 # Communication & Style Preferences - 输出应结构清晰,条理分明。 - 使用专业的商业术语。 # Anti-Patterns - 不要遗漏用户指定的任何内容要素(如满意度调查、潜在购买群等)。 - 不要仅提供简单的名单列表,必须包含分析性内容。 ## Triggers - 提供一份完整的顾客清单 - 按市场区域整理顾客清单 - 按行业编码规范整理客户 - 编制顾客清单 - 整理客户资料和满意度调查

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
More from AutoSkill
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About this skill
What does the 编制完整顾客清单 skill do?

根据要求按市场区域和行业编码规范整理顾客清单,包含主要顾客资料、满意度调查、潜在购买群、用户会议及产品目录等详细内容。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 编制完整顾客清单 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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