App智能巡检(异动报告)

Query UApp (友盟+) application outlier reports, yesterday anomalies, and intelligent inspection summaries. Use when users ask about app anomaly detection, outl...

UApp Outlier Detection

Query 友盟+ (UApp) application anomaly data including outlier reports, daily anomalies, and intelligent inspection summaries.

Authentication

Obtain credentials in priority order:

1. User input: User directly provides apiKey (ak) and apiSecurity (sk)
2. Config file: Read from umeng-config.json on user's machine
3. Environment variables: Get UMENG_API_KEY and UMENG_API_SECURITY from environment

Reading umeng-config.json

Search common locations for umeng-config.json:

• Current working directory
• User home directory (~)
• Project root directories

Expected format:

{
  "apiKey": "your_api_key",
  "apiSecurity": "your_api_security",
  "apps": {
    "appkey1": "AppName1",
    "appkey2": "AppName2"
  }
}

The apps section maps app names to appkeys. When a user provides an app name instead of an appkey, the skill will look it up in this mapping.

If credentials not found, ask the user to provide them.

Resolving App Name to Appkey

When the user provides an app name instead of an appkey:

1. Check if input looks like an appkey (hex string, 20+ chars) - if so, use directly
2. Look up in the apps mapping from umeng-config.json
3. If not found, ask the user to provide the correct appkey

Example:

• User says "查询 APM_Demo_iOS 的异动报告" -> look up "APM_Demo_iOS" in apps mapping -> get appkey
• User says "查询 59892f08310c9307b60023d0 的异动报告" -> use appkey directly

If the app cannot be resolved, ask the user: "无法找到应用 'xxx' 对应的 appkey，请提供正确的 appkey 或在 umeng-config.json 中添加应用映射。"

API Endpoints

1. Get App Outlier Report

Query outlier/anomaly report for a specific app on a given date.

Endpoint: GET https://mobile.umeng.com/ht/api/v3/ai/getOutlierPoints

Parameters:

• ak: API key
• sk: API security token
• appkey: Application key
• ds: Date in yyyyMMdd format (e.g., 20260401)

Example:

import requests

url = "https://mobile.umeng.com/ht/api/v3/ai/getOutlierPoints?ak={apiSecret}&sk={apiSecurity}&appkey=59892f08310c9307b60023d0&ds=20260401"

payload = {}
headers = {
   'User-Agent': 'Apifox/1.0.0 (https://apifox.com)',
   'Accept': '*/*',
   'Host': 'mobile.umeng.com',
   'Connection': 'keep-alive'
}
response = requests.request("GET", url, headers=headers, data=payload)
print(response.text)

Response fields (in data object, keyed by appkey):

• appKey: Application key
• shareUrl: Report URL - open this to view detailed outlier report
• id: Outlier point ID
• category: Outlier summary description (e.g., "活跃低于周三常态")
• type: Outlier type - green: green point, red: red point
• ds: Date when outlier occurred (YYYY-MM-DD format)
• status: 1 = anomaly, 2 = normal

2. Get Yesterday's Outliers

Check which applications had anomalies yesterday.

Endpoint: GET https://mobile.umeng.com/ht/api/v3/ai/getYesterdayOutliers

Parameters:

• ak: API key
• sk: API security token

Example:

import requests

url = "https://mobile.umeng.com/ht/api/v3/ai/getYesterdayOutliers?ak={apiSecret}&sk={apiSecurity}"

payload = {}
headers = {
   'User-Agent': 'Apifox/1.0.0 (https://apifox.com)',
   'Accept': '*/*',
   'Host': 'mobile.umeng.com',
   'Connection': 'keep-alive'
}
response = requests.request("GET", url, headers=headers, data=payload)
print(response.text)

Response fields (in data array):

• name: Application name
• appkey: Application key
• platform: Platform (e.g., "iphone")
• todayActiveUser: Today's active users
• todayNewUser: Today's new users
• todayTotalUser: Today's total users
• activeUser: Active users
• newUser: New users
• totalUser: Total users
• launch: Launch count
• todayLaunch: Today's launch count
• appLevel: App level
• productLevel: Product level (e.g., "PLUS")
• star: Whether starred
• outlierTip: Outlier reminder info
  • id: Outlier point unique ID
  • type: Outlier type - green or red
  • ds: Outlier date
  • status: 1 = anomaly, 2 = normal

3. Get Intelligent Inspection Summary

Retrieve basic intelligent inspection information for the account.

Endpoint: GET https://mobile.umeng.com/ht/api/v3/claw/meta/aiEventSummary

Headers:

• Authorization: Bearer {apiSecurity} (use sk value)

Example:

import requests

url = "https://mobile.umeng.com/ht/api/v3/claw/meta/aiEventSummary"

payload = {}
headers = {
   'Authorization': 'Bearer {apiSecurity}',
   'User-Agent': 'Apifox/1.0.0 (https://apifox.com)',
   'Accept': '*/*',
   'Host': 'mobile.umeng.com',
   'Connection': 'keep-alive'
}

response = requests.request("GET", url, headers=headers, data=payload)
print(response.text)

Response fields:

• metas: Tracking anomaly reporting info for last 30 days
  • err_code: Error code (see Error Code Reference below)
  • error_count: Error count
• eventSummary: Event summary
  • normal: Normal (calculing + partially calculated) event count
  • stopped: Stopped calculation event count
  • unReg: Unregistered time count
• noEventQuotaAppNames: Applications without event quota
• unRegEvents: Unregistered event identifiers

Error Code Reference

Error Code	Description
100001	Event ID is null
100002	Event ID is empty or all spaces
100003	Event ID conflicts with system reserved events
100004	Event ID exceeds 128 bytes
100005	Event ID contains invalid characters
100006	Event properties count exceeds limit
100007	Property key conflicts with system reserved properties
100008	iOS key type is invalid
100009	Property key exceeds 128 bytes
100010	Property value is empty @""
100011	Property value is null
100012	Property value exceeds 256 bytes
100013	iOS property value type is invalid
100014	Property parameter type is invalid
100015	Property count is 0
100016	Property key is empty @""
100020	Event duration exceeds limit
100022	Label parameter value exceeds 256 bytes
100023	Event API property value is null
100024	Property key is null
100025	Property key contains invalid characters
100026	Android property value type is invalid
200002	Event ID/name is duplicated
200001	Event count exceeds limit
200003	Property key/name is duplicated

Usage Workflow

Query Specific App Outlier Report

1. Get credentials (ak, sk) using authentication priority
2. Get appkey from user input
3. Get ds (date) - if user says "yesterday", calculate yesterday's date in yyyyMMdd format
4. Call endpoint 1 (Get App Outlier Report)
5. Present results:
   • If status = 1: Report the anomaly with category, type, and provide the shareUrl
   • If status = 2: Report that the app is normal for that date
   • Provide the shareUrl for detailed report viewing

Check Yesterday's Anomalies

1. Get credentials (ak, sk)
2. Call endpoint 2 (Get Yesterday's Outliers)
3. Present results:
   • List apps with outlierTip.status = 1 (anomalies)
   • Include app name, platform, outlier type (green/red), and category if available
   • If no anomalies, report that all apps are normal

Get Intelligent Inspection Summary

1. Get credentials (sk for Bearer token)
2. Call endpoint 3 (Get Intelligent Inspection Summary)
3. Present results:
   • Summarize event status (normal, stopped, unregistered counts)
   • List any tracking anomalies from metas with error codes and counts
   • Translate error codes using the Error Code Reference table
   • List apps without event quota if any

Response Handling

• Always translate error codes to user-friendly descriptions using the Error Code Reference
• Provide shareUrl directly so users can open detailed reports
• Distinguish between green (绿点) and red (红点) outlier types
• Format dates consistently (YYYY-MM-DD for display, yyyyMMdd for API calls)
• If API returns non-200 status or error, report the error message to the user

Usage Statistics

This skill reports usage statistics via umeng-cli trace command after each API call.

Requirements

Requires umeng-cli to be installed. Install via:

npm install -g @umengfe/umeng-cli

Control Statistics

Disable statistics via environment variable:

export UMENG_ENABLE_STATS=false

Statistics Data Collected

• skill_name: Always "uapp-outlier"
• event_type: Which API was called (outlier_report, yesterday_outliers, inspection_summary)
• appkey: Application key (if applicable)
• Additional context (e.g., date for outlier reports)

No sensitive data (credentials, response data, user queries) is collected.