Docker Agent: Running and Operating Agents
SkillCloud & infraHelps your agent launch itself inside Docker with the right approval settings, covering docker claude skill setup.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Docker Agent: Running and Operating Agents skill
About this skill
Use this skill when running a Docker Agent with `docker agent run`, choosing a safety/approval mode, using the `--sandbox` isolation flag, setting up aliases, or troubleshooting a run (missing credentials, worktrees). Even if the user just says they want to "run my agent", "make my agent auto-approv
What this skill tells your AI
The instructions your AI receives, as published by docker/skills in skills/docker-agent-run/SKILL.md and read by ahel’s review.
Overview
This skill owns the operational side of Docker Agent: invoking docker agent run against a local config, an alias, or a registry reference; choosing how
much autonomy the agent gets over tool calls; isolating it in a sandbox VM;
and diagnosing why a run fails. It assumes the agent.yaml already exists —
see Related skills for authoring it.
When to use this skill
Activate this skill when:
- The user wants to run an agent interactively or headlessly (
--exec). - The user is choosing or debugging
--safety,--yolo, or approval behavior for tool calls. - The user wants to isolate an agent's shell/filesystem access with
--sandbox, or hit a sandbox network-policy error. - The user wants a reusable shortcut (
docker agent alias), a scoped git worktree (--worktree), or is debugging credentials/model availability (docker agent doctor).
Do not use this skill when
Do not use this skill when:
- The task uses standalone
sbx run/create/stop/rmrather thandocker agent run --sandbox— usedocker-sandboxes-lifecycle. - The task is standalone
sbx policyorsbx secretconfiguration — usedocker-sandboxes-network-credentials. Establish which CLI is in use before recommending commands when the request only says "my sandbox". - The task is writing or editing the
agent.yamlitself (models, toolsets, sub_agents) — usedocker-agent-config. - The task is exposing an agent as a server (
serve), sharing it via a registry (share), or evaluating it (eval) — usedocker-agent-deploy.
Core guidance
Safety modes
docker agent runsupports four--safetymodes; choose the least permissive one that still lets the task finish:strict— ask for approval before every tool call.balanced— auto-approve calls classified as safe, ask for the rest.restricted— auto-approve safe calls, deny the rest outright. Use for unattended/CI runs where no human can answer a prompt.autonomous— approve everything automatically. Equivalent to--yolo.
- Never default an unattended run (cron, CI, a server endpoint) to
autonomous/--yolo. Userestrictedfor unattended runs so an unexpected tool call fails closed instead of running unreviewed; reserveautonomous/--yolofor a sandboxed or fully trusted interactive session.# CI-safe: unreviewed tool calls are denied, not silently approved. docker agent run --exec --safety restricted ./agent.yaml "Triage the failing test" - Bake a safety default into an alias so callers don't have to remember it,
and note that an explicit CLI
--safety/--yoloondocker agent runstill overrides the alias:docker agent alias add safe-coder myorg/coder --safety balanced
Sandbox isolation
--sandboxruns the agent inside an isolated microVM managed by thesbxCLI (a separate prerequisite — install and configure it first). All shell, filesystem, and process activity started by built-in toolsets happens inside the VM; only the working directory (and, unless--no-kit, a staged "kit" of skills/prompt files) is mounted in. Exception: a local stdio MCP server declared on the agent runs as a host process outside the sandbox VM — treat any such MCP server as a trusted host integration, not a sandboxed one.docker agent run --sandbox ./agent.yaml- The sandbox network proxy is default-deny: only the model provider,
models.dev, and hosts the toolset resolver can infer are open. A custom MCP server or third-party API often needs an explicit allowlist entry — add it permanently rather than re-discovering it every run:docker agent sandbox allow api.example.com docker agent sandbox list docker agent sandbox deny api.example.com - Prefer baking
runtime: {sandbox: true}into the agent's ownagent.yamlover remembering--sandboxon every invocation of that agent; an explicit--sandbox=falseon the CLI still overrides the config default for a single debug run. - Sandboxes persist and are reused across runs from the same workspace — they are not torn down when the session ends. Don't expect a clean VM on every run; if you need one, change the mount set (e.g. a new kit) to force recreation.
Aliases and default agent
- Register a shortcut once, then run it by name instead of a path:
docker agent alias add code myorg/notion-expert docker agent run code - For a local run with no agent argument,
docker agent rundiscoversdocker-agent.yaml, thendocker-agent.yml, thendocker-agent.hclin the current directory (first match wins). Only if none exists does it resolve thedefaultalias, falling back to the built-in default agent. Theagent.yamlexamples in these skills pass a filename explicitly;agent.yamlis not an auto-discovery name. - Set the fallback for directories without a project config with a
defaultalias. To select it even when a project config exists, passdefaultexplicitly:docker agent alias add default ./my-agent.yaml docker agent run default - CLI flags on
docker agent run <alias>always override the alias's own stored options (e.g.docker agent run yolo-coder --yolo=false).
Worktrees
- Use
--worktree(-w) to isolate an agent's file edits from your current checkout — it runs the agent inside a fresh git worktree. For an interactive session, a clean worktree (no uncommitted changes, untracked files, or new commits) is removed automatically when the session ends; one with work prompts you to keep or remove. A headless run (--exec) never auto-cleans its worktree, regardless of state — it is left in place for inspection:docker agent run ./agent.yaml --worktree=auth-refactor --worktree-base origin/main --worktreecannot be combined with--remoteor--sandbox. To resume a worktree run, pass--session -1(or the session id) — do not re-pass--worktree, which fails because the worktree already exists.
Troubleshooting
- "No model is currently available" or "model ... is not pulled" means the
agent's provider has no usable credential, or (for
dmr/) the model hasn't been pulled. Rundocker agent doctor ./agent.yamlfirst — it reports the resolved model/provider and whether credentials were found — before touching the YAML. If credentials are missing, export the provider's API key; if a DMR model is missing, rundocker model pull <model>. Rerundoctorbefore retrying the task. - An agent that only describes a plan instead of executing it is usually
missing the tool it needs (add
type: shellortype: todoinagent.yaml), not a model failure — hand this back todocker-agent-config. - A
403 Blocked by network policyerror inside a sandbox run means the destination isn't allowlisted; usedocker agent sandbox allow <host>.
Related skills
- For standalone
sbxlifecycle commands, usedocker-sandboxes-lifecycle. - For standalone
sbx policyandsbx secret, usedocker-sandboxes-network-credentials. - For writing or changing the underlying
agent.yaml(models, toolsets, sub_agents), usedocker-agent-config. - For serving, sharing, or evaluating the agent, use
docker-agent-deploy.
References
references/safety-and-sandbox.md— full safety-mode/flag interaction table and sandbox trust-boundary details.references/sources.md— provenance of every rule in this skill.
Assets
- None.
Checks
checks/verification.md— Verification runbook for adocker agent runinvocation.
Signals
- GitHub stars
- 410
- Forks
- 21
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
docker-agent-run- Source
- github.com/docker/skills