datadog-cli 精选
Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.
安装方式
cp -r cli-tool/components/skills/ai-research/datadog-cli ~/.claude/skills/datadog-cli把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/
https://raw.githubusercontent.com/davila7/claude-code-templates/b84033e51002cd4c805d5dce27e6d1fe19cb95f1/cli-tool/components/skills/ai-research/datadog-cli/SKILL.md下载后另存为 ~/.claude/skills/datadog-cli/SKILL.md。链接锁定采集时的 commit,内容与本站展示一致。
整仓一次性获取:git clone --depth 1 https://github.com/davila7/claude-code-templates.git
依赖与权限
- 需要 API Key —— 使用前需配置相应的密钥环境变量
- 需要联网访问外部服务
- 依赖外部命令:
npx - 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。
SKILL.md 正文
Datadog CLI
A CLI tool for AI agents to debug and triage using Datadog logs and metrics.
Required Reading
You MUST read the relevant reference docs before using any command:
- [Log Commands](references/logs-commands.md)
- [Metrics](references/metrics.md)
- [Query Syntax](references/query-syntax.md)
- [Workflows](references/workflows.md)
- [Dashboards](references/dashboards.md)
Setup
Environment Variables (Required)
export DD_API_KEY="your-api-key"
export DD_APP_KEY="your-app-key"
Get keys from: https://app.datadoghq.com/organization-settings/api-keys
Running the CLI
npx @leoflores/datadog-cli <command>
For non-US Datadog sites, use --site flag:
npx @leoflores/datadog-cli logs search --query "*" --site datadoghq.eu
Commands Overview
| Command | Description |
|---|---|
logs search | Search logs with filters |
logs tail | Stream logs in real-time |
logs trace | Find logs for a distributed trace |
logs context | Get logs before/after a timestamp |
logs patterns | Group similar log messages |
logs compare | Compare log counts between periods |
logs multi | Run multiple queries in parallel |
logs agg | Aggregate logs by facet |
metrics query | Query timeseries metrics |
errors | Quick error summary by service/type |
services | List services with log activity |
dashboards | Manage dashboards (CRUD) |
dashboard-lists | Manage dashboard lists |
Quick Examples
Search Errors
npx @leoflores/datadog-cli logs search --query "status:error" --from 1h --pretty
Tail Logs (Real-time)
npx @leoflores/datadog-cli logs tail --query "service:api status:error" --pretty
Error Summary
npx @leoflores/datadog-cli errors --from 1h --pretty
Trace Correlation
npx @leoflores/datadog-cli logs trace --id "abc123def456" --pretty
Query Metrics
npx @leoflores/datadog-cli metrics query --query "avg:system.cpu.user{*}" --from 1h --pretty
Compare Periods
npx @leoflores/datadog-cli logs compare --query "status:error" --period 1h --pretty
Global Flags
| Flag | Description |
|---|---|
--pretty | Human-readable output with colors |
--output <file> | Export results to JSON file |
--site <site> | Datadog site (e.g., datadoghq.eu) |
Time Formats
- Relative:
30m,1h,6h,24h,7d - ISO 8601:
2024-01-15T10:30:00Z
Incident Triage Workflow
# 1. Quick error overview
npx @leoflores/datadog-cli errors --from 1h --pretty
# 2. Is this new? Compare to previous period
npx @leoflores/datadog-cli logs compare --query "status:error" --period 1h --pretty
# 3. Find error patterns
npx @leoflores/datadog-cli logs patterns --query "status:error" --from 1h --pretty
# 4. Narrow down by service
npx @leoflores/datadog-cli logs search --query "status:error service:api" --from 1h --pretty
# 5. Get context around a timestamp
npx @leoflores/datadog-cli logs context --timestamp "2024-01-15T10:30:00Z" --service api --pretty
# 6. Follow the distributed trace
npx @leoflores/datadog-cli logs trace --id "TRACE_ID" --pretty
See [workflows.md](references/workflows.md) for more debugging workflows.
质量与来源
- 所属仓库
- davila7/claude-code-templates
- 仓库星标
- 3.3 万
- 最近更新
- 今天
- 采集时间
- 今天
- commit
- b84033e51002
- 内容指纹
- sha256:d65cdb0087a7043
- 文件路径
- cli-tool/components/skills/ai-research/datadog-cli/SKILL.md
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agent-management
Create, manage, and orchestrate AI agents using the AI Maestro CLI. Use when the user asks to "create agent", "list agents", "delete agent", "hibernate agent", "wake agent", "install plugin", "show agent", "restart agent", or any agent lifecycle management task.
agent-messaging
Send and receive cryptographically signed messages between AI agents using the Agent Messaging Protocol (AMP). Use when the user asks to "send a message to an agent", "check agent inbox", "message another agent", "reply to a message", "notify an agent", or any inter-agent communication task.
docs-search
Search auto-generated codebase documentation for function signatures, API docs, class definitions, and code comments. Use when the user asks to "search docs", "find documentation", "look up a function", "check the API", or before implementing changes to verify correct signatures and patterns.
graph-query
Query the code graph database to understand component relationships, dependencies, and change impact. Use when the user asks to "find callers", "check dependencies", "what uses this", "show relationships", "find serializers", or when reading code and needing to understand what depends on a component before modifications.
memory-search
Search conversation history and semantic memory to recall previous discussions, decisions, and context. Use when the user asks to "search memory", "what did we discuss", "remember when", "find previous conversation", "check history", or before starting work to recall prior decisions.
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