arkcli-onboard

An onboarding workflow for connecting a model from Volcengine Ark to an app or service. It turns a broad request into an ordered set of checks and setup steps.

In plain words
What is it for?
It helps connect supported text, image, or video models, check model and endpoint details, and guide deployment-related setup.
Why use it?
It prevents confusion between trying a model, deploying one, and configuring access, while routing each step to the right ArkCLI skill.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/volcengine/ark-cli/arkcli-onboard
Any agent
npx skills add volcengine/ark-cli --skill arkcli-onboard
Clone the repo
git clone --depth 1 https://github.com/volcengine/ark-cli

Made for: Claude Code, Codex.

Per session 200 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,004 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00200 $0.02004
Opus 5 $0.00100 $0.01002
Sonnet 5 $0.00040 $0.00401
Haiku 4.5 $0.00020 $0.00200

Measured 2d ago against content hash e0fa4c705030, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 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.

skills/arkcli-onboard/SKILL.md · 82 lines

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--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先让用户确认选哪个 ─► 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

Read the full file on GitHub · 82 lines

Files

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.

Changes

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.

  1. 2d ago First seen · 82 lines · 200 tokens per session scan A e0fa4c705030

Subscribe to this mod's changes

arkcli-onboard is a skill published in the GitHub repository volcengine/ark-cli (112 stars, last pushed 5d ago), licensed Apache-2.0. It adds 200 tokens to every session and 2,004 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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