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SkillHub ClubAnalyze Data & AIFull StackData / AI

datadog-cli

Use this skill when you need to search Datadog logs, query metrics, tail logs in real-time, trace distributed requests, investigate errors, compare time periods, find log patterns, check service health, or export observability data.

Packaged view

This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
79
Hot score
93
Updated
March 20, 2026
Overall rating
C3.0
Composite score
3.0
Best-practice grade
A88.4

Install command

npx @skill-hub/cli install jjmartres-opencode-datadog

Repository

jjmartres/opencode

Skill path: opencode/skill/datadog

Use this skill when you need to search Datadog logs, query metrics, tail logs in real-time, trace distributed requests, investigate errors, compare time periods, find log patterns, check service health, or export observability data.

Open repository

Best for

Primary workflow: Analyze Data & AI.

Technical facets: Full Stack, Data / AI.

Target audience: everyone.

License: MIT.

Original source

Catalog source: SkillHub Club.

Repository owner: jjmartres.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install datadog-cli into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/jjmartres/opencode before adding datadog-cli to shared team environments
  • Use datadog-cli for development workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.

Original source / Raw SKILL.md

---
name: datadog-cli
description: "Use this skill when you need to search Datadog logs, query metrics, tail logs in real-time, trace distributed requests, investigate errors, compare time periods, find log patterns, check service health, or export observability data."
license: MIT
compatibility: opencode
---

# Datadog

This skill will help you to interact with Datadog, through the unofficial datadog-cli to search Datadog logs, query metrics, tail logs in real-time, trace distributed requests, investigate errors, compare time periods, find log patterns, check service health, or export observability data.

## When to Use This Skill

- Trigger phrases include:
  - "search logs"
  - "tail logs"
  - "query metrics"
  - "check Datadog"
  - "find errors"
  - "trace request"
  - "compare errors"
  - "what services exist"
  - "log patterns"
  - "CPU usage"
  - "service health"
  - "get service activity"

## How to Use

### Log Search

```bash
datadog logs search --query "<query>" [--from <time>] [--to <time>] [--limit <n>] [--sort <order>]
```

**Examples:**

```bash
datadog logs search --query "status:error" --from 1h
datadog logs search --query "service:api status:error @http.status_code:500" --from 1h
```

### Live Tail (Real-time Streaming)

Stream logs as they arrive. Press Ctrl+C to stop.

```bash
datadog logs tail --query "<query>" [--interval <seconds>]
```

**Examples:**

```bash
datadog logs tail --query "status:error"
datadog logs tail --query "service:api" --interval 5
```

### Trace Correlation

Find all logs for a distributed trace across services.

```bash
datadog logs trace --id "<trace-id>" [--from <time>] [--to <time>]
```

**Example:**

```bash
datadog logs trace --id "abc123def456" --from 24h
```

### Log Context

Get logs before and after a specific timestamp to understand what happened.

```bash
datadog logs context --timestamp "<iso-timestamp>" [--before <time>] [--after <time>] [--service <svc>]
```

**Examples:**

```bash
datadog logs context --timestamp "2024-01-15T10:30:00Z" --before 5m --after 2m
datadog logs context --timestamp "2024-01-15T10:30:00Z" --service api --before 10m
```

### Error Summary

Quick breakdown of errors by service, type, and message.

```bash
datadog errors [--from <time>] [--to <time>] [--service <svc>]
```

**Examples:**

```bash
datadog errors --from 1h
datadog errors --service payment-api --from 24h
```

### Period Comparison

Compare log counts between current period and previous period.

```bash
datadog logs compare --query "<query>" --period <time>
```

**Examples:**

```bash
datadog logs compare --query "status:error" --period 1h
datadog logs compare --query "service:api status:error" --period 6h
```

### Log Patterns

Group similar log messages to find patterns (replaces UUIDs, numbers, etc.).

```bash
datadog logs patterns --query "<query>" [--from <time>] [--limit <n>]
```

**Examples:**

```bash
datadog logs patterns --query "status:error" --from 1h
datadog logs patterns --query "service:api" --from 6h --limit 1000
```

### Service Discovery

List all services with recent log activity.

```bash
datadog services [--from <time>] [--to <time>]
```

**Example:**

```bash
datadog services --from 24h
```

### Log Aggregation

```bash
datadog logs agg --query "<query>" --facet <facet> [--from <time>]
```

**Common facets:** `status`, `service`, `host`, `@http.status_code`, `@error.kind`

**Examples:**

```bash
datadog logs agg --query "*" --facet status --from 1h
datadog logs agg --query "status:error" --facet service --from 24h
```

### Multiple Queries

Run multiple queries in parallel.

```bash
datadog logs multi --queries "name1:query1,name2:query2" [--from <time>]
```

**Example:**

```bash
datadog logs multi --queries "errors:status:error,warnings:status:warn" --from 1h
```

### Metrics Query

```bash
datadog metrics query --query "<metrics-query>" [--from <time>] [--to <time>]
```

**Query format:** `<aggregation>:<metric>{<tags>}`

**Examples:**

```bash
datadog metrics query --query "avg:system.cpu.user{*}" --from 1h
datadog metrics query --query "avg:system.cpu.user{service:api}" --from 1h
datadog metrics query --query "sum:trace.http.request.errors{service:api}.as_count()" --from 1h
```

## 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`

## Common Workflows

### Incident Triage

```bash
# 1. Quick error overview
datadog errors --from 1h

# 2. Is this new? Compare to previous period
datadog logs compare --query "status:error" --period 1h

# 3. What patterns are we seeing?
datadog logs patterns --query "status:error" --from 1h

# 4. Narrow down by service
datadog logs search --query "status:error service:payment-api" --from 1h

# 5. Get context around a specific timestamp
datadog logs context --timestamp "2024-01-15T10:30:00Z" --service api --before 5m --after 2m

# 6. Follow the distributed trace
datadog logs trace --id "TRACE_ID"
```

### Real-time Debugging

```bash
# Stream errors as they happen
datadog logs tail --query "status:error"

# Watch specific service
datadog logs tail --query "service:api status:error"
```

### Service Health Check

```bash
# List services
datadog services --from 24h

# Check error distribution
datadog logs agg --query "service:api" --facet status --from 1h

# Check CPU/memory
datadog metrics query --query "avg:system.cpu.user{service:api}" --from 1h
```

### Export for Sharing

```bash
# Save search results
datadog logs search --query "status:error" --from 1h --output errors.json

# Save error summary
datadog errors --from 24h --output error-report.json
```

## Datadog Query Syntax

| Operator | Example | Description |
|----------|---------|-------------|
| `AND` | `service:api status:error` | Both conditions |
| `OR` | `status:error OR status:warn` | Either condition |
| `-` | `-status:info` | Exclude |
| `*` | `service:api-*` | Wildcard |
| `>=` `<=` | `@http.status_code:>=400` | Numeric comparison |
| `[TO]` | `@duration:[1000 TO 5000]` | Range |

### Common Attributes

- `service` - Service name
- `status` - Log level (error, warn, info, debug)
- `host` - Hostname
- `@http.status_code` - HTTP status code
- `@error.kind` - Error type
- `@trace_id` / `@dd.trace_id` - Trace ID
datadog-cli | SkillHub