元数据 (必填)
name: data-analysis
version: "1.0.0"
description: 分析结构化数据并生成统计报告和可视化建议
author: ExoProtocolDemo
定价 (必填)
pricing:
model: per_call
price_lamports: 30000
运行时要求 (必填)
runtime:
docker_image: exo-runtime-python-3.11
docker_image_hash: sha256:mno567pqr890...
entrypoint: scripts/main.py
timeout_seconds: 60
输入输出 Schema (必填)
io:
input_schema:
type: object
properties:
data:
type: array
description: 数据数组（JSON 格式）
items:
type: object
maxItems: 10000
columns:
type: array
description: 要分析的列名（可选，默认分析全部）
items:
type: string
analysis_types:
type: array
description: 分析类型
items:
type: string
enum: ["descriptive", "correlation", "distribution", "outliers", "trends"]
default: ["descriptive"]
group_by:
type: string
description: 分组字段（可选）
required:
- data
additionalProperties: false
maxProperties: 20
output_schema:
type: object
properties:
statistics:
type: object
description: 描述性统计
correlations:
type: object
description: 相关性分析
outliers:
type: array
description: 异常值检测结果
visualization_suggestions:
type: array
description: 推荐的可视化类型
insights:
type: array
description: 自动发现的数据洞察
Tool Annotations - 行为注解
annotations:
readOnlyHint: true
destructiveHint: false
idempotentHint: true
openWorldHint: false
Data Analysis Skill
功能描述
对结构化数据进行统计分析，自动检测异常值，计算相关性，并提供可视化建议。
适用场景:
- 数据探索性分析 (EDA)
- 业务指标分析
- 异常检测
- 报表生成
使用示例
输入:
{
"data": [
{"date": "2024-01-01", "revenue": 1000, "users": 50},
{"date": "2024-01-02", "revenue": 1200, "users": 55},
{"date": "2024-01-03", "revenue": 950, "users": 48},
{"date": "2024-01-04", "revenue": 1500, "users": 70},
{"date": "2024-01-05", "revenue": 1100, "users": 52}
],
"columns": ["revenue", "users"],
"analysis_types": ["descriptive", "correlation", "outliers"]
}
输出:
{
"statistics": {
"revenue": {
"count": 5,
"mean": 1150,
"std": 202.48,
"min": 950,
"max": 1500,
"median": 1100
},
"users": {
"count": 5,
"mean": 55,
"std": 8.37,
"min": 48,
"max": 70,
"median": 52
}
},
"correlations": {
"revenue_users": {
"coefficient": 0.96,
"interpretation": "strong_positive"
}
},
"outliers": [
{"column": "users", "value": 70, "index": 3, "z_score": 1.79}
],
"visualization_suggestions": [
{"type": "line_chart", "columns": ["date", "revenue"], "reason": "时序数据适合折线图"},
{"type": "scatter_plot", "columns": ["users", "revenue"], "reason": "强相关性适合散点图"}
],
"insights": [
"revenue 与 users 呈强正相关 (r=0.96)",
"2024-01-04 的 users 值 (70) 偏高，可能为异常值或特殊事件"
]
}
注意事项
- 数据量限制 10000 条记录
- 仅支持数值型列的统计分析
- 相关性分析需要至少 2 列数值数据
- 异常值检测基于 Z-score (|Z| > 1.5 标记为潜在异常)
