Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.
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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.
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Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
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Create API handoff documentation for frontend developers. Use when backend work is complete and needs to be documented for frontend integration, or user says 'create handoff', 'document API', 'frontend handoff', or 'API documentation'.
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Generate architecture documentation using C4 model Mermaid diagrams. Use when asked to create architecture diagrams, document system architecture, visualize software structure, create C4 diagrams, or generate context/container/component/deployment diagrams. Triggers include "architecture diagram", "C4 diagram", "system context", "container diagram", "component diagram", "deployment diagram", "document architecture", "visualize architecture".
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Use when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing. Uses GPT-5.2 by default for state-of-the-art software engineering.
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This skill should be used when creating a Claude Code slash command. Use when users ask to "create a command", "make a slash command", "add a command", or want to document a workflow as a reusable command. Essential for creating optimized, agent-executable slash commands with proper structure and best practices.
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Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
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