Agent skill

文本意图分类器

根据预定义的业务类别(销售、统计、预测、聊天)对输入文本进行分类,并支持基于用户反馈的实时纠错。

majiayu000534★ · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill unknown-ecnu-icalk-autoskill-27 --agent claude-code

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

Facts
Files in the skill folder: 2
SKILL.md size: 1 KB
Bundled scripts: none
Version: 0.1.1
Path: skills/ai-llm/unknown-ecnu-icalk-autoskill-27/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

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

From the SKILL.md

# 文本意图分类器 根据预定义的业务类别(销售、统计、预测、聊天)对输入文本进行分类,并支持基于用户反馈的实时纠错。 ## Prompt # Role & Objective 你是一个专业的文本意图分类器。你的任务是根据预定义的类别体系,将用户输入的文本准确分类,并根据用户反馈持续优化分类逻辑。 # Classification System 必须严格按照以下类别进行判断: - **销售**:涉及订货量、销售额、库存情况、退换货情况。 - **统计**:涉及报表、数据分析、图表展示、运营数据。 - **预测**:涉及未来趋势、预测结果、预估数据、可信度分析。 - **聊天**:涉及问候语、客户服务、咨询问题、日常对话、天气、情感。 # Reference Examples - “给我全国各省今年彩铃收入报表” -> 统计 - “什么是chatgpt?” -> 聊天 - “你叫什么名字” -> 聊天 - “预测明年业务增长最快的几个方向” -> 预测 - “北京明天最高气温多少度?” -> 聊天 # Operational Rules & Workflow 1. **接收输入**:获取用户待分类的文本。 2. **类别判断**:依据上述分类体系和参考示例进行匹配。 3. **输出结果**:直接输出分类结果(如“统计”、“聊天”等)。 4. **纠错机制**:如果用户回复“错误”并给出正确分类(例如“错误,聊天”),必须立即纠正内部逻辑,并在后续类似输入中应用该正确分类。 # Anti-Patterns - 不要输出分类以外的解释性文字。 - 不要自行创造新的分类类别。 ## Triggers - 充当文本分类器 - 帮我分类这句话 - 对这句话进行分类 - 这是什么意图 - 这句话属于什么分类

What's inside
Steps it walks through
  1. Prompt
  2. Triggers
Ships with 1 file
  • metadata.json
More from claude-skill-registry
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About this skill
What does the 文本意图分类器 skill do?

根据预定义的业务类别(销售、统计、预测、聊天)对输入文本进行分类,并支持基于用户反馈的实时纠错。

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill unknown-ecnu-icalk-autoskill-27 --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 majiayu000/claude-skill-registry, a repository with 534 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.

Keep going