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pup小狗

Agent Skill

pup 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

545

周安装

8

GitHub Stars

12

下载量

65
CodexClaudeCursorGemini CLI

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:pup(小狗)
来源仓库:https://github.com/arjunmahishi/dotfiles
仓库路径:skills/pup
安装命令:
npx skills add https://github.com/arjunmahishi/dotfiles --skill pup
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/arjunmahishi/dotfiles --skill pup

简介

pup 是 Datadog API 的命令行包装工具,专用于查询日志、指标数据及元信息检索。

  • 适合在需要分析系统性能、排查异常事件或监控业务指标时快速获取观测数据。
  • 支持 metrics query/search/list 等子命令,分别对应不同粒度的时序数据操作需求。
  • 使用前需配置有效的 Datadog API key 并确保网络可访问其服务端点。
  • pup 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Purpose

Use this skill when you need to query Datadog for observability data: searching logs, querying time-series metrics, aggregating log statistics, listing available metrics, or inspecting metric metadata. pup is a CLI wrapper around Datadog APIs.

When to use what

Metrics

  • pup metrics query: Query time-series metric data with aggregation, filtering, and grouping. Primary command for metric analysis.
  • pup metrics search: Same query syntax as query but uses the simpler v1 API. Use when you don't need v2 timeseries formula semantics.
  • pup metrics list: Discover available metric names. Use with --filter to narrow by pattern.
  • pup metrics metadata get: Read metadata (description, unit, type) for a specific metric.
  • pup metrics tags list: List available tags for a specific metric.

Logs

  • pup logs query: Query logs using the v2 API (recommended). Supports timezone and flexible sorting.
  • pup logs search: Search logs using the v1 API. Simpler but less capable than query.
  • pup logs list: List logs with basic filtering. Lightest-weight log retrieval.
  • pup logs aggregate: Statistical analysis on logs -- count, avg, percentile, cardinality, grouped by field.

Core concepts

  • Output format: Use -o table for human-readable output, -o json for machine-readable. Default is json.
  • Time ranges: --from and --to accept relative values (1h, 30m, 7d, 1w, 1M) or absolute unix timestamps. --to defaults to now.
  • Metric query syntax: <aggregation>:<metric_name>{<filter>} [by {<group>}]

- Aggregations: avg, sum, min, max, count - Filters: tag key-value pairs like {env:prod}, {host:web-*}, or {*} for all - Grouping: by {service}, by {host,env}

  • Log query syntax: Uses Datadog search syntax

- By field: status:error, service:web-app, host:i-* - By attribute: @http.status_code:500, @user.id:12345 - Boolean: AND, OR, NOT, negation with -status:info - Phrase: "exact phrase" - Wildcard: host:i-*

Recommended workflow

Investigating a metric

  1. Discover metrics: pup metrics list --filter="<pattern>" to find relevant metric names.
  2. Inspect metadata: pup metrics metadata get <metric> to understand unit and type.
  3. Check tags: pup metrics tags list <metric> to see available dimensions.
  4. Query data: pup metrics query --query="avg:<metric>{<filter>} by {<group>}" --from="1h"

Investigating logs

  1. Start broad: pup logs search --query="status:error" --from="1h" --limit=10 to see recent errors.
  2. Narrow down: Add filters like service:X AND @http.status_code:500.
  3. Aggregate for patterns: pup logs aggregate --query="status:error" --from="1h" --compute="count" --group-by="service" to find which services are failing.
  4. Deep dive: pup logs query --query="service:failing-svc AND status:error" --from="1h" --limit=100 for full log details.

Important tips

  • Prefer -o json when processing output programmatically; use -o table when presenting to users.
  • For log searches, --limit defaults to 50 (max 1000 for search, configurable for query/list).
  • Metric queries return time-series arrays with timestamps -- the data points are in the series field of the JSON output.
  • Log aggregate --compute supports: count, avg(@field), sum(@field), min(@field), max(@field), cardinality(@field), percentile(@field, N).
  • Use --group-by with aggregate to break down results by any log field or attribute.
  • Time ranges are relative to now: 1h means "1 hour ago to now", 7d means "7 days ago to now".

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

35.57%
按下载量换算23

Claude

29.68%
按下载量换算19

Cursor

18.39%
按下载量换算12

Gemini CLI

10.75%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。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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