Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/volcengine/ark-cli/arkcli-deploynpx skills add volcengine/ark-cli --skill arkcli-deploygit clone --depth 1 https://github.com/volcengine/ark-cliWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00208 | $0.02849 |
| Opus 5 | $0.00104 | $0.01425 |
| Sonnet 5 | $0.00042 | $0.00570 |
| Haiku 4.5 | $0.00021 | $0.00285 |
Grade A, and why
arkcli-deploy scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
arkcli +deploy
前置: 先用 Read 读 ../arkcli-shared/SKILL.md 获取共享认证/配置/写操作守卫规则。
新增 flag --set-default <modality>: 部署成功后自动把新 endpoint 设为 active profile 该 modality (text / image / video) 的默认资源。仅在真实部署成功且用户明确传 modality 时生效;失败仅 stderr warn,不阻断部署主流程。详见 ../arkcli-shared/references/profile-defaults.md。
写操作 + 计费:+deploy 创建在线推理 Endpoint 是真实写操作,会产生计费资源。该工作流依赖在线探测,不支持 --dry-run;执行前必须与用户显式确认最终参数。
模型开通是独立计费写动作,非交互环境一律不自动开通:若目标基础模型尚未开通,+deploy 会触发"开通模型"(账号级计费写)。在 agent / CI / 管道这类非 TTY 环境,开通被硬拒——--yes 也不放行(--yes 只在真人交互终端里用于跳过 [y/N])。命中时 CLI 返回 model_activation_required + console 链接,你必须结束本轮、把"开通(计费)"这件事连同链接交还给真人,由真人在交互终端确认或在网页 console 开通。严禁自己补 --yes / echo Y / 设 ARKCLI_ALLOW_HEADLESS_ACTIVATION 替用户开通——你打印一句"请确认"然后同一轮自己加 --yes 跑掉,等于没问。ARKCLI_ALLOW_HEADLESS_ACTIVATION=1 只留给真·无人值守自动化(CI 流水线),不是 agent 该设的。
实名前置(开通类硬闸门):+deploy 会触发开通模型,第一步先 arkcli auth status 读 volc_sso.identity.verified——false 即停并把实名页 https://console.volcengine.com/user/authentication/detail/ 贴给用户、暂停等待(详见 ../arkcli-auth/references/realname-gate.md)。不要先试 +deploy、撞到 model-id 无效 / 模型未开通报错再回头查实名——那些报错会把你带偏。
语音模型硬边界:TTS / ASR / 配音 / 朗读 / 播客 / 音色设计 / 实时语音交互,或模型名命中 doubao-seed-tts-*、doubao-seed-asr-*、seedasr-* 时,不要执行 +deploy。这些模型在 arkcli 当前只支持 models search 做广场发现;不能创建 Endpoint,也不能通过开通模型绕过。
示例代码:+deploy 创建后自动渲染 + 独立命令 +code-example
两条路径都可用,都走 OpenTOP OpenGetSampleCode:
+deploy创建成功后自动渲染:把该接入点的多语言调用示例写到./ark-examples/<ep-id>/(用 ep-id 当作可直接调用的 model id,示例直接调你刚建的接入点),并在 stderr 打一行落盘摘要。best-effort —— 取不到示例只软提示,不影响 Endpoint 创建/启动。- 独立命令
arkcli +code-example:按基础模型名/版本单独生成示例,转../arkcli-code-example/SKILL.md;注意它按 model-version 提供,部分版本后端无 group 会返回 not found,缺失时再降级到ark-examples/静态示例或方舟控制台示例代码页。
子命令穷举(只有这一个)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 87 lines · 208 tokens per session scan A 963b31ec17c7
arkcli-deploy is a skill published in the GitHub repository volcengine/ark-cli (112 stars, last pushed 5d ago), licensed Apache-2.0. It adds 208 tokens to every session and 2,849 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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