What changed
Agent mode transforms five aspects of the CLI for machine consumption:
- JSON output by default: All data retrieval commands (
list,get,query, etc.) return JSON instead of tables, without needing the-o jsonflag. - Structured help: The
--helpflag returns a JSON object with command metadata, flags, subcommands, and usage patterns, so agents can discover capabilities programmatically. - Structured errors: Errors are emitted as JSON objects on
stderr, with separate error and hint fields that agents can parse and act on. - No confirmation prompts: Destructive operations like delete and remove skip interactive prompts automatically, just as if the
--forceflag were passed. - No ANSI colors: All escape codes are suppressed like with the
--color noneflag, so output is clean for downstream parsing.
Zero-configuration activation
Agent mode auto-activates when it detects a known AI agent environment variable. It recognizes Claude Code, Cursor, Windsurf, Cline, Aider, GitHub Copilot, OpenAI Codex, and any MCP server session.
For explicit control, enable it with the --agent-mode flag or the DASH0_AGENT_MODE=true environment variable, and DASH0_AGENT_MODE=false to override and disable.
Why this matters
When an AI coding agent queries your dashboards, investigates error logs, or applies asset definitions, it needs structured, predictable output — not tables padded for terminal width. Agent mode removes that friction. The CLI becomes a tool that agents can drive as naturally as a human types commands, with every response machine-readable by default.
Combined with the comprehensive command reference, consistent naming conventions, and profile-based authentication, the Dash0 CLI is designed to be the interface between your AI coding agent and your observability platform.