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datadog-analyser数据狗分析仪

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。

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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:datadog-analyser(数据狗分析仪)
来源仓库:https://github.com/delexw/claude-code-misc
仓库路径:skills/datadog-analyser
安装命令:
npx skills add https://github.com/delexw/claude-code-misc --skill datadog-analyser
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/delexw/claude-code-misc --skill datadog-analyser

简介

用于调查和分析 Datadog 可观测性数据,支持日志和指标分析。

  • 通过 pup CLI 工具实现查询、过滤和数据汇总功能。
  • 需传入查询参数和时间范围,自动转换为 epoch 秒数进行检索。
  • 适用于故障排查、性能回归分析和运维监控场景。
  • datadog-analyser 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Datadog Analyser

Investigate and analyse Datadog observability data using the pup CLI.

Inputs

Raw arguments: $ARGUMENTS

Infer from the arguments:

  • QUERY: what to analyse.
  • SINCE: (optional) UTC ISO8601 start of analysis window. When provided, convert to epoch seconds for pup --from flags (e.g. date -d "2026-03-20T02:30:00Z" +%s on Linux, or date -jf "%Y-%m-%dT%H:%M:%SZ" "2026-03-20T02:30:00Z" +%s on macOS).
  • UNTIL: (optional) UTC ISO8601 end of analysis window. When provided, convert to epoch seconds for pup --to flags where supported; otherwise omit (defaults to now).
  • SERVICE_HINT: (optional) Service name to prioritise in queries (filter monitors, logs, APM by this service first).

System Requirements

  • pup CLI installed — see https://github.com/datadog-labs/pup/blob/main/README.md
  • DD_API_KEY and DD_APP_KEY environment variables set. Important: When checking these variables, verify at least 2 times before concluding they are not set. Environment variables can appear unset due to shell context differences. Never expose the values — use existence checks only (e.g. test -n "$DD_API_KEY").
  • DD_SITE set if not using datadoghq.com (optional)

Output Directory

.datadog-analyser-tmp/
└── report.md    # Final analysis report

Execution

1. Verify Connection

Run pup test to confirm the CLI is configured and connected:

pup test

If this fails, use AskUserQuestion to inform the user that pup is not configured or DD_API_KEY/DD_APP_KEY are not set, and link to the setup guide: https://github.com/datadog-labs/pup/blob/main/README.md

Do NOT continue until pup test succeeds.

2. Discover Available Commands

Run pup agent guide to get the full list of available commands and usage patterns for this session:

pup agent guide

If pup agent guide is not available (command not found), use the known command reference below and continue.

3. Analyse

Based on QUERY, determine which pup commands are most relevant. Use --output=json (default) for all commands to get structured output. Run commands sequentially.

Time window rule — when QUERY contains a named day ("today", "yesterday") or a calendar range, compute the window using local day boundaries, not UTC calendar days. A user saying "today" means since local midnight, so an event at 11am local is included even if it falls on a different UTC date.

For relative durations ("last 1h", "last 24h"), pass them directly as pup relative strings: --from="1h", --from="24h".

For named days, compute the local day boundary as epoch seconds and pass to --from/--to:

# Start of local today as epoch (Linux / macOS)
date -d "$(date +%Y-%m-%d) 00:00:00" +%s          # Linux
date -jf "%Y-%m-%d %H:%M:%S" "$(date +%Y-%m-%d) 00:00:00" +%s  # macOS
# Current time as epoch
date +%s
# Start of local yesterday
date -d "$(date -d yesterday +%Y-%m-%d) 00:00:00" +%s          # Linux
date -jf "%Y-%m-%d %H:%M:%S" "$(date -v-1d +%Y-%m-%d) 00:00:00" +%s  # macOS

When SINCE and UNTIL are provided as UTC ISO8601, convert each to epoch seconds and use them for all --from/--to flags instead of inferring time windows from QUERY. This ensures all Datadog queries cover exactly the same window as the other PIR sub-skills:

# Linux
SINCE_EPOCH=$(date -d "2026-03-20T02:30:00Z" +%s)
UNTIL_EPOCH=$(date -d "2026-03-20T06:00:00Z" +%s)
# macOS
SINCE_EPOCH=$(date -jf "%Y-%m-%dT%H:%M:%SZ" "2026-03-20T02:30:00Z" +%s)
UNTIL_EPOCH=$(date -jf "%Y-%m-%dT%H:%M:%SZ" "2026-03-20T06:00:00Z" +%s)

When SERVICE_HINT is provided, prioritise it in queries:

  • Filter monitors: pup monitors search --query="service:<SERVICE_HINT>"
  • Scope log searches with service:<SERVICE_HINT> in the query string
  • Focus APM traces on that service first

Common analysis patterns:

GoalCommands
Triggered/alerting monitorspup monitors list, pup monitors search --query="status:alert"
Error logspup logs search --query="status:error" --from="1h"
Metric trendpup metrics query --query="<metric>" --from="<window>"
Active incidentspup incidents list
SLO healthpup slos list, pup slos status <id>
APM service healthpup apm services, pup apm dependencies
Security signalspup security signals list, pup security findings search
Error trackingpup error-tracking issues search --query="<service>"
Synthetics failurespup synthetics tests list
CI failurespup cicd pipelines list, pup cicd events list

All commands default to JSON output. Use flags like --from, --to, --query, --tags to narrow scope. Refer to pup <command> --help for available flags.

4. Report

All timestamps in the report must use current agent's local timezone (detect via system clock), not UTC. Format: 2026-03-20 15:30 NZDT (with TZ abbreviation). Do NOT use UTC in user-facing report sections — this includes timestamps that come directly from API responses (e.g. last_triggered, overall_state_modified, event times). Convert every timestamp to local time before writing it to the report.

Write a structured analysis to .datadog-analyser-tmp/report.md using the Write tool:

  1. Summary — Overall health status and key findings
  2. Details — Breakdown of findings per domain (monitors, logs, metrics, etc.)
  3. Anomalies — Anything alerting, degraded, or unusual
  4. Recommendations — Suggested follow-up actions

Inform the user of the report location: .datadog-analyser-tmp/report.md

适合场景

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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

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能力 4

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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。

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敏感数据

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安装前确认

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