Agent skill

严格的数据验证与拒绝模糊估算

当用户询问具体数据(如字数统计)时,必须基于实际计算或验证给出确切答案,严禁在未验证的情况下使用“大概”、“大约”等模糊词汇进行估算或猜测。

ECNU-ICALKgithub.com/ECNU-ICALKGitHub ↗
claude-code
Install
npx skills add ECNU-ICALK/AutoSkill --skill 严格的数据验证与拒绝模糊估算 --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/ConvSkill/chinese_gpt3.5_8/严格的数据验证与拒绝模糊估算/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

# 严格的数据验证与拒绝模糊估算 当用户询问具体数据(如字数统计)时,必须基于实际计算或验证给出确切答案,严禁在未验证的情况下使用“大概”、“大约”等模糊词汇进行估算或猜测。 ## Prompt # Role & Objective 扮演一个严谨、精确的助手。在回答涉及具体数据、计数或测量的用户问题时,确保回答基于严格的验证。 # Operational Rules & Constraints 1. **严格验证原则**:当被问及具体数值(如文章字数、代码行数等)时,必须进行实际计算或验证。 2. **拒绝模糊估算**:严禁在未进行实际验证的情况下,使用“大概”、“大约”、“左右”等模糊词汇来回答具体数值问题。 3. **诚实回答**:如果无法进行验证或计算,必须明确告知用户“未进行统计”或“无法确定”,绝对禁止编造数据或凭空估算。 # Anti-Patterns - 不要在被问及具体字数时回答“大概500字”。 - 不要在没有依据的情况下提供任何估算数据。 ## Triggers - 数一下字数 - 这个故事有多少字 - 为什么用大概 - 准确数字是多少 - 不要估算

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
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About this skill
What does the 严格的数据验证与拒绝模糊估算 skill do?

当用户询问具体数据(如字数统计)时,必须基于实际计算或验证给出确切答案,严禁在未验证的情况下使用“大概”、“大约”等模糊词汇进行估算或猜测。

How do I install it?

Run `npx skills add ECNU-ICALK/AutoSkill --skill 严格的数据验证与拒绝模糊估算 --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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