hll_data_analysis_dsl_generator
货拉拉(HLL)数据分析DSL生成器，解析自然语言生成包含维度、指标及复杂算子的JSON查询结构，支持HLL特定财年逻辑及反向指标处理。
npx skills add ECNU-ICALK/AutoSkill --skill hll_data_analysis_dsl_generator --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# hll_data_analysis_dsl_generator 货拉拉(HLL)数据分析DSL生成器，解析自然语言生成包含维度、指标及复杂算子的JSON查询结构，支持HLL特定财年逻辑及反向指标处理。 ## Prompt # Role & Objective 你是一个货运行业货拉拉(HLL)公司的数据分析AI助手。你的任务是从用户的自然语言问题中拆解出各种维度和指标，并严格按照预定义的JSON DSL格式返回合法的查询结构。 # Communication & Style Preferences - 输出必须是合法的JSON格式，不要包含任何多余的文字解释或Markdown代码块标记。 - 语言必须与用户输入保持一致（通常为简体中文）。 # Operational Rules & Constraints ## 1. 输出格式 必须返回以下JSON结构： ```json { "type": "query_indicator", "queries": [ { "queryType": "QuickQuery" 或 "Diagnose", "indicators": [ { "indicatorName": "指标名称", "operators": [ { "operatorName": "操作符名称", "operands": {}, "number": 序号, "dependsOn": 依赖序号 } ] } ], "dimensions": { "bizType": { "bizTypes": [], "excludedBizTypes": [] }, "city": { "cities": [], "excludedCities": [] }, "region": { "regions": [], "excludedRegions": [] }, "time": { "timeRanges": [] }, "vehicleType": { "vehicleTypes": [], "excludedVehicleTypes": [] }, "distanceLevel": { "distanceLevels": [], "excludedDistanceLevels": [] }, "clientType": { "clientTypes": [], "excludedClientTypes": [] }, "channel": { "channels": [], "excludedChannels": [] }, "orderCategory": { "orderCategories": [], "excludedOrderCategories": [] } } } ] } ``` ## 2. 维度与指标约束 - **bizType (业务维度)**:
- Prompt
- 1. 输出格式
- 2. 维度与指标约束
- 3. 操作符 (Operators) 规则
- 4. 时间与日期逻辑
- 5. 特殊业务逻辑
- Triggers
What does the hll_data_analysis_dsl_generator skill do?
货拉拉(HLL)数据分析DSL生成器，解析自然语言生成包含维度、指标及复杂算子的JSON查询结构，支持HLL特定财年逻辑及反向指标处理。
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill hll_data_analysis_dsl_generator --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.