Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/volcengine/ark-clinpx agentmods add skills/volcengine/ark-cli/arkcli-onboardWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/volcengine/ark-cli/arkcli-onboard)<a href="https://agentmods.dev/skills/volcengine/ark-cli/arkcli-onboard"><img src="https://agentmods.dev/badge/skills/volcengine/ark-cli/arkcli-onboard/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/volcengine/ark-cli/arkcli-onboard"><img src="https://agentmods.dev/badge/skills/volcengine/ark-cli/arkcli-onboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00200 | $0.02042 |
| Opus 5.5 | $0.00080 | $0.00817 |
| Sonnet 5.5 | $0.00040 | $0.00408 |
| Haiku 4.5 | $0.00020 | $0.00204 |
Grade A, and why
arkcli-onboard 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 1mo 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
arkcli 接入向导（workflow）
CRITICAL — 开始前 MUST 先用 Read 工具读取 ../arkcli-shared/SKILL.md（认证闸门、命令选择顺序、写操作安全边界）。
本 skill 只负责编排顺序与分支。 每一步的私有命令细节（如
+deploy的--model/--name/ JSON 字段，models search的过滤）都在对应能力 skill 里，本文不重复。本文只允许出现跨命令通用的安全护栏（只在叶子命令支持时使用 Client Preview，否则只读核对 + 明确确认）；一旦出现某个命令的私有 flag 说明，就是越界。
离线 / --help 验证模式
- 用户已给出模型且明确禁止远端查询时，跳过 Step 1 的实际
models search/get；不得为了“验证流程”偷偷查询模型或 Endpoint。 - Step 2 即使只查看帮助，也必须保留当前产品的资源范围语义：运行
arkcli infer endpoint list --mine --help，不能退化成无范围的list --help，也不能换成--page-all。 --help模式只验证命令选择，不执行创建、部署、登录或任何真实资源查询。
它解决什么
用户表达的是意图级目标（"我想在服务里用豆包"），而不是命令级目标（"部署一个 endpoint"）。这类口语通常不会命中 arkcli-deploy 的关键词，但本质就是"正式接入 = 需要一个可复用的 Endpoint"。本 skill 把这个意图固化成一条有序、有分支、可回归的链路，逐步 delegate 给 owning skill。
触发 vs 不触发
- ✅ "我想在我的 app/服务里用豆包" / "怎么把方舟模型接到我的服务" / "帮我接入 seedream" / "想正式用上某模型"
- ❌ 语音模型接入 / TTS / ASR / 配音 / 朗读 / 播客 / 音色 / 实时语音交互，或模型名命中
doubao-seed-tts-*、doubao-seed-asr-*、seedasr-*→ 不走本向导；只转arkcli-models做广场发现，并说明当前 arkcli 不支持语音模型调用、部署、示例、用量、费用或接入向导 - ❌ 用户已说"部署 / 创建 endpoint / deploy" → 直接走
arkcli-deploy（已在 deploy 意图里，不必经本向导） - ❌ 只想"试效果 / 问一句 / 生成一张图" →
+chat/+gen（试用不需要 Endpoint） - ❌ 只想"看示例代码"且已知模型名 → 直接
arkcli-code-example
编排（每步 delegate，不抄细节）
Step 0 认证 + 实名闸门
└─► 见 arkcli-shared「认证闸门」；命中开通/部署意图先做实名检查
（../arkcli-auth/references/realname-gate.md）
Step 1 选模型
└─► arkcli-models（search / get）。用户没指定模型就先帮选、确认再继续
└─ 命中语音模型（TTS / ASR / 播客 / 音色 / 实时语音交互）即停：
只说明广场可搜，当前 arkcli 不支持继续接入
Step 2 查是否已有可复用 Endpoint ★必查★
└─► arkcli-infer-endpoint：list --mine（"我的"语义见
../arkcli-auth/references/identity-resolution.md）
├─ 有 EP 且【绑定目标模型/版本】+【状态可用(如 Running)】
│ 多个匹配或不确定时按本轮结果结构化选一个 ─► 跳到 Step 4（复用其 endpoint-id）
└─ 无匹配 EP（账号下只有别的模型的 EP 不算匹配）─► Step 3
Step 3 创建 Endpoint ★唯一写操作★
└─► arkcli-deploy：只读核对 + 与用户确认，再真建（不支持 --dry-run）
（二次确认协议见 arkcli-shared）
Step 4 (可选) 生成调用示例
└─► arkcli-code-example：按 model-version 提供，覆盖不全；
缺失时降级到方舟控制台示例页，不当作失败报给用户
Step 5 回执
└─► 给出 endpoint-id + 一句话"怎么在代码里用它"，回到用户原始目标
What ships with it
1 file 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.
- 1mo ago Changed e9b4144526d5
- 1mo ago First seen · 82 lines · 200 tokens per session scan A e0fa4c705030
arkcli-onboard is a skill published in the GitHub repository volcengine/ark-cli (143 stars, last pushed 8d ago), licensed Apache-2.0. It adds 200 tokens to every session and 2,042 once invoked, about $0.0008 per session on Opus 5.5. 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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