From datadog-cli
CLI for searching Datadog logs, querying metrics, tracing requests, summarizing errors, and managing dashboards during production debugging and observability triage.
npx claudepluginhub softaworks/agent-toolkit --plugin datadog-cliThis skill uses the workspace's default tool permissions.
A CLI tool for AI agents to debug and triage using Datadog logs and metrics.
Queries and analyzes Datadog logs, metrics, APM traces, and monitors via API. Useful for debugging production issues, monitoring app performance, and investigating alerts.
Investigates production issues by querying Datadog logs, metrics, and APM traces, then correlating findings with codebase. Useful for debugging errors, latency spikes, alerts in deployed services.
Executes Datadog operations (metrics, logs, monitors, dashboards) via pup CLI or generates API integration code for TypeScript, Python, Java, Go, Rust.
Share bugs, ideas, or general feedback.
A CLI tool for AI agents to debug and triage using Datadog logs and metrics.
You MUST read the relevant reference docs before using any command:
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
npx @leoflores/datadog-cli <command>
For non-US Datadog sites, use --site flag:
npx @leoflores/datadog-cli logs search --query "*" --site datadoghq.eu
| 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 |
npx @leoflores/datadog-cli logs search --query "status:error" --from 1h --pretty
npx @leoflores/datadog-cli logs tail --query "service:api status:error" --pretty
npx @leoflores/datadog-cli errors --from 1h --pretty
npx @leoflores/datadog-cli logs trace --id "abc123def456" --pretty
npx @leoflores/datadog-cli metrics query --query "avg:system.cpu.user{*}" --from 1h --pretty
npx @leoflores/datadog-cli logs compare --query "status:error" --period 1h --pretty
| Flag | Description |
|---|---|
--pretty | Human-readable output with colors |
--output <file> | Export results to JSON file |
--site <site> | Datadog site (e.g., datadoghq.eu) |
30m, 1h, 6h, 24h, 7d2024-01-15T10:30:00Z# 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 for more debugging workflows.