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研究检索敏感数据github未标认证来源可访问许可证需确认审计提醒

data-health-monitor数据健康监控

Agent Skill

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

总安装

465

周安装

19

GitHub Stars

2

下载量

150
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:data-health-monitor(数据健康监控)
来源仓库:https://github.com/lytics/agent-skills
仓库路径:skills/data-health-monitor
安装命令:
npx skills add https://github.com/lytics/agent-skills --skill data-health-monitor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/lytics/agent-skills --skill data-health-monitor

简介

聚合数据流、作业、模式和配额等多维度健康指标,输出统一诊断报告。

  • 纯只读操作,不影响现有数据处理流程,快速定位异常源头。
  • 需配置 LYTICS_API_TOKEN 和 API_URL,默认指向 https://api.lytics.io 。
  • 建议定期运行检查,特别关注 schema 变更和事件配额超限风险。
  • data-health-monitor 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Data Health Monitor

Purpose

Answers "is my data flowing correctly?" with a single command. Aggregates health signals across streams, jobs, schema, and event quota into a unified, actionable report. Purely read-only.

Environment

  • LYTICS_API_TOKEN -- API authentication token
  • LYTICS_API_URL -- Base URL (default: https://api.lytics.io)

Flow

Run all four health checks, then present a unified report. If the user asks about a specific area, focus on that dimension but still show a summary of others.

Check 1: Stream Health

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/stream" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

For each stream, evaluate:

SignalHow to DetectSeverity
Activelast_msg_ts within last hourHEALTHY
Stale (continuous)last_msg_ts 1-24 hours agoWARNING
Stale (batch)last_msg_ts 2-7 days agoWARNING
Deadlast_msg_ts > 24h ago (continuous) or > 7d (batch)ERROR
Never receivedct == 0ERROR

Distinguish batch vs continuous by checking if the stream has associated jobs with periodic schedules.

For streams with issues, fetch recent stats for more detail:

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/stream/${STREAM_NAME}/stats" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Check 2: Job Health

# Active jobs (default: non-terminal states)
curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/job" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

# Also check recently failed jobs
curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/job?show_completed=true" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Evaluate each job:

StatusSeverityAction
runnableHEALTHYRunning normally
sleepingHEALTHYScheduled, waiting for next run
pausedWARNINGIntentional but flag for awareness
faultERRORNeeds investigation -- fetch logs
failedERRORTerminal failure -- fetch logs
killedINFOManually stopped

For faulted/failed jobs, fetch logs:

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/job/${JOB_ID}/logs" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Also check for stale jobs: if a runnable job hasn't been updated in over 1 hour, it may be stuck.

Check 3: Schema Health

# Get all fields with metadata
curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/schema/user/field" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Check:

  • Identity fields: Count fields where IsIdentifier == true. Flag if fewer than 2.
  • PII fields: Count fields marked IsPII == true for awareness.
  • Stale fields: Fields with Modified timestamp older than 30 days that are actively used.

For deeper coverage analysis:

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/api/schema/user/fieldinfo" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Check field presence/absence ratios. Flag fields with very low coverage that appear in segment FilterQL.

Check 4: Event Quota

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/control/eventquota/thresholds" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Report current usage against thresholds (50%, 75%, 100%, 125%).

Optional: Metrics Deep Dive

When the user wants trends or deeper analysis:

# Stream throughput over last 24h
curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/metric?dimension=stream&range=now-24h" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

# Job execution metrics over last 24h
curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/metric?dimension=works&range=now-24h" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

# Segment size trends
curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/metric?dimension=segment&range=now-24h" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Present as trends: "Stream throughput is down 40% vs yesterday" or "Segment sizes are stable."

Output Format

Present the report as:

## Data Health Report

### Overall: HEALTHY | NEEDS ATTENTION | UNHEALTHY

### Streams (N total)
  HEALTHY: X streams actively receiving data
  WARNING: 'stream_name' -- last event 3 days ago
  ERROR: 'stream_name' -- never received events

### Jobs (N active)
  HEALTHY: X jobs running normally
  FAULT: 'job_name' -- error message from logs
  PAUSED: 'job_name' -- paused since date

### Schema (user table, N fields)
  Identity fields: N configured (field1, field2, ...)
  Low coverage: 'field' at X%
  Stale: 'field' not updated in N days

### Event Quota
  Current usage: X% of monthly quota

### Recommendations
1. Specific actionable recommendation
2. Another recommendation
3. ...

Severity Logic

Overall StatusCriteria
HEALTHYAll streams active, all jobs running, no faults, quota < 75%
NEEDS ATTENTIONAny: stale streams, paused jobs, low-coverage fields, quota 75-100%
UNHEALTHYAny: faulted/failed jobs, dead streams, quota > 100%

Recommendations Engine

Generate specific, actionable recommendations based on findings:

  • Faulted job → "Investigate 'job_name' fault. Check auth credentials or bounce the job."
  • Dead stream → "Stream 'name' hasn't received data in N days. Check the source integration."
  • Zero-event stream → "Stream 'name' is configured but has never received data. Verify the integration is set up correctly."
  • Low identity fields → "Only N identity fields configured. Consider marking additional fields as identifiers for better profile resolution."
  • Quota approaching → "Event quota at X%. Consider reviewing high-volume streams or upgrading your plan."
  • Stale field → "Field 'name' hasn't been updated in N days. Check if the source integration is still active."

Error Handling

  • API errors on any check: Report the error for that dimension, continue with other checks. Never let one failed check block the whole report.
  • Empty responses: Report "No [streams/jobs/fields] found" -- this may indicate a new or unconfigured account.
  • Timeout: If a check takes too long, skip it with a note and proceed.

Dependencies

  • Composes: stream-inspector skill, job-manager skill, schema-manager skill
  • References: ../references/api-client.md

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.71%
按下载量换算57

Claude

27.18%
按下载量换算41

Cursor

17.98%
按下载量换算27

Gemini CLI

9.59%
按下载量换算14

安全审计

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通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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