Guizang Social Cards
op7418/guizang-social-card-skill
Produces social card sets for Xiaohongshu and WeChat: carousels, Live Photo motion cards and puzzle layouts, and WeChat cover pairs, rendered from single-file HTML.
arkcli 自定义模型仓库管理：从 TOS 导入自定义模型、查询/筛选自定义模型、查看详情、改名、删除、查询可用量化模式、量化已就绪的模型。任何提到自定义模型 ID（cm-）的管理、部署准备，或要求用 cm- 直接对话/推理/试效果的边界判断，都必须使用本 skill。注意：查询火山公共基础模型（doubao 等 foundation models）走 arkcli-models；本…
Install Arkcli Custommodel
$ npx skills add volcengine/ark-cli --skill arkcli-custommodel -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install volcengine/ark-cli arkcli-custommodel --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/volcengine/ark-cli.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/arkcli-custommodel .claude/skills/arkcli-custommodel && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "arkcli-custommodel" agent skill from https://github.com/volcengine/ark-cli/tree/main/skills/arkcli-custommodel into .claude/skills/arkcli-custommodel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "arkcli-custommodel", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/volcengine/ark-cli/tree/main/skills/arkcli-custommodelType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add volcengine/ark-cli --skill arkcli-custommodel -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install volcengine/ark-cli arkcli-custommodel --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/volcengine/ark-cli.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/arkcli-custommodel .agents/skills/arkcli-custommodel && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "arkcli-custommodel" agent skill from https://github.com/volcengine/ark-cli/tree/main/skills/arkcli-custommodel into .agents/skills/arkcli-custommodel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "arkcli-custommodel", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add volcengine/ark-cli --skill arkcli-custommodel -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install volcengine/ark-cli arkcli-custommodel --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/volcengine/ark-cli.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/arkcli-custommodel .cursor/skills/arkcli-custommodel && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "arkcli-custommodel" agent skill from https://github.com/volcengine/ark-cli/tree/main/skills/arkcli-custommodel into .cursor/skills/arkcli-custommodel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "arkcli-custommodel", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/volcengine/ark-cli.git --path skills/arkcli-custommodel--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add volcengine/ark-cli --skill arkcli-custommodel -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install volcengine/ark-cli arkcli-custommodel --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/volcengine/ark-cli.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/arkcli-custommodel .gemini/skills/arkcli-custommodel && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "arkcli-custommodel" agent skill from https://github.com/volcengine/ark-cli/tree/main/skills/arkcli-custommodel into .gemini/skills/arkcli-custommodel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "arkcli-custommodel", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install volcengine/ark-cli arkcli-custommodelInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add volcengine/ark-cli --skill arkcli-custommodel -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/volcengine/ark-cli.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/arkcli-custommodel .github/skills/arkcli-custommodel && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "arkcli-custommodel" agent skill from https://github.com/volcengine/ark-cli/tree/main/skills/arkcli-custommodel into .github/skills/arkcli-custommodel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "arkcli-custommodel", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add volcengine/ark-cli --skill arkcli-custommodel -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install volcengine/ark-cli arkcli-custommodel --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/volcengine/ark-cli.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/arkcli-custommodel .opencode/skills/arkcli-custommodel && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "arkcli-custommodel" agent skill from https://github.com/volcengine/ark-cli/tree/main/skills/arkcli-custommodel into .opencode/skills/arkcli-custommodel/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "arkcli-custommodel", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
arkcli-custommodel- GitHub stars
- 140
- Token cost
- ~2.6k tokens
- SKILL.md length
- 635 words
- Files
- 9 (incl. references)
- Skills in repo
- 25
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
arkcli 自定义模型仓库管理：从 TOS 导入自定义模型、查询/筛选自定义模型、查看详情、改名、删除、查询可用量化模式、量化已就绪的模型。任何提到自定义模型 ID（cm-）的管理、部署准备，或要求用 cm- 直接对话/推理/试效果的边界判断，都必须使用本 skill。注意：查询火山公共基础模型（doubao 等 foundation models）走 arkcli-models；本…
- Works in 4 steps: 从 TOS 上传新自定义模型 → 量化已就绪的自定义模型 → 准备给 +deploy 当目标 → …
- Media & Creative work in your project
- SKILL.md covers 守卫与使用原则, 适用场景, 反唤起信号 and cm-* 直接推理边界, plus 10 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Arkcli Custommodel is an agent skill from volcengine/ark-cli. arkcli 自定义模型仓库管理：从 TOS 导入自定义模型、查询/筛选自定义模型、查看详情、改名、删除、查询可用量化模式、量化已就绪的模型。任何提到自定义模型 ID（cm-）的管理、部署准备，或要求用 cm- 直接对话/推理/试效果的边界判断，都必须使用本 skill。注意：查询火山公共基础模型（doubao 等 foundation models）走 arkcli-models；本 skill 只管账号下的自定义模型仓库。
Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/arkcli-custommodel-available-quantizations.md`, `references/arkcli-custommodel-delete.md` and `references/arkcli-custommodel-get.md`).
It sits in Media & Creative. The repository describes itself as: The fastest way to put Volcengine Ark in your terminal and your AI agent — go from prompt to generated media, multimodal answer, or deployed endpoint in a single command, no API… The licence is Apache-2.0.
When your agent uses it
- Media & Creative work in your project
Example prompts
- “/arkcli-custommodel”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit fb5b7be. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Arkcli Custommodel loads about 2.6k tokens when it runs, and up to ~7.3k if it reads all its reference files. Until then it costs about 61 tokens; SKILL.md has 635 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from volcengine/ark-cli at commit fb5b7be, republished under its Apache-2.0 licence (© volcengine). 635 words, ~2,566 tokens.
Download SKILL.mdSave it as
.claude/skills/arkcli-custommodel/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.- name
- arkcli-custommodel
- description
- arkcli 自定义模型仓库管理：从 TOS 导入自定义模型、查询/筛选自定义模型、查看详情、改名、删除、查询可用量化模式、量化已就绪的模型。任何提到自定义模型 ID（`cm-*`）的管理、部署准备，或要求用 `cm-*` 直接对话/推理/试效果的边界判断，都必须使用本 skill。注意：查询火山**公共基础模型**（doubao 等 foundation models）走 arkcli-models；本 skill 只管账号下的自定义模型仓库。
- version
- 1.0.1
- metadata.cliHelp
- arkcli models custommodel --help
arkcli models custommodel
CRITICAL — 开始前 MUST 先用 Read 工具读取 ../arkcli-shared/SKILL.md，其中包含认证闸门、配置排查与共享安全规则
CRITICAL — 所有 models custommodel 命令在执行之前，务必先用 Read 工具读取其对应的 reference 文档，禁止直接盲目调用命令。
CRITICAL — 写操作（upload / update / delete / quantize）必须先确认用户意图。删除前必须确认是否还有 endpoint 引用。
守卫与使用原则
- 自定义模型相关需求优先使用
arkcli models custommodel ... - 这些命令虽然是标准 CLI 类型，但实现入口仍然来自
shortcuts/models/ - 只有产品命令无法覆盖时，才回退到
../arkcli-api-explorer/SKILL.md - 本 skill 不是基础模型查询入口；基础模型目录查询转
../arkcli-models/SKILL.md - 写操作和异步任务必须把影响范围、轮询方式和后续动作串起来，不要停在单条命令
适用场景
- 把训练好/微调好的权重从 veTOS 导入到 ARK 自定义模型
- 查询账号下已有的自定义模型（"我的自定义模型有哪些 / 状态如何"）
- 查看自定义模型详情、产物形态、活跃 endpoint 引用
- 修改自定义模型展示名或描述
- 删除不再使用的自定义模型
- 把已
ready的自定义模型量化，准备给+deploy当目标
反唤起信号
- 找官方基础模型 → 用
../arkcli-models/SKILL.md的search/list/get - 直接调用自定义模型推理 → 必须先
+deploy，再走+chat/+gen - 触发模型微调任务（customization job 本身）→ 转
../arkcli-train-finetune/SKILL.md - 从精调任务的 step（
global_step_N）注册成cm-(=「导出训练产物」)→ 转../arkcli-train-finetune/SKILL.md的arkcli train finetune artifacts list / export，不要用本 skill 的upload(那是给"用户自己的 TOS 文件"用的,后端 ActionUploadModel;mcj 输出走CreateCustomModel,完全不同的 API) - 已经拿到 endpoint-id 后想管理 endpoint → 转
../arkcli-infer-endpoint/SKILL.md
cm-* 直接推理边界
- 用户要求“用
cm-*直接对话/推理/试效果”时也必须加载本 skill。明确说明cm-*是自定义模型资源 ID，不能直接传给+chat/+gen；推理前需要单独获得或部署 Endpoint。 - 该请求本身不授权部署、查询账号下 Endpoint 或发起推理。未经用户继续授权，不执行
arkcli +deploy、arkcli +chat、arkcli infer endpoint list，也不拼接jq等扫描方案。 - 只说明边界和下一步选择；用户明确要求继续部署后，才转
../arkcli-deploy/SKILL.md并遵守其确认流程。
核心概念
- 本 skill 统一把
arkcli models custommodel ...管理的资源称为自定义模型（CustomModel，ID 形如cm-xxxxx）；它与../arkcli-models/SKILL.md中search/list/get操作的官方基础模型（FoundationModel）是两套独立资源 - 自定义模型来源有两类：
import—— 用户从 TOS 上传权重导入(本 skillupload命令,走UploadModelAPI)customization—— 通过模型微调任务产出(走../arkcli-train-finetune/SKILL.md的train finetune artifacts export,底层是另一个 OpenAPI ActionCreateCustomModel,跟upload不互通)
- 生命周期状态机：
preparation → processing → ready（成功）或failed；导出场景另有exporting/exportfailed - 量化是单独流程：先
available-quantizations <id>查可用模式，并查看supported_inference_types_by_quantization预判每种量化方式支持的部署/付费形态；再quantize <id> --quantization <mode>提交量化任务，结果是一个独立的新 cm-xxxxx。源模型、量化结果模型、最终部署出来的 endpoint 是三类不同资源，不能混用 ID - 自定义模型 ID（
cm-xxxxx）不是<name>-<primary_version>形式，不能直接作为+chat/+gen的--model；必须先通过arkcli +deploy获得 endpoint，拿ep-xxx才能调用推理。若该自定义模型已有 Running Endpoint，+deploy会直接复用已有 endpoint
快速决策
- 用户问"我的自定义模型"：读
references/arkcli-custommodel-list.md，用arkcli models custommodel list --mine - 用户要按名称 / ID / base 模型 display name 模糊查找：读
references/arkcli-custommodel-list.md，用list --search <kw> - 用户已有
cm-xxxxx并要状态 / 详情 / endpoint 引用 / artifact types：读references/arkcli-custommodel-get.md，用get - 用户要从 TOS 导入权重：读
references/arkcli-custommodel-upload.md。用户已有tos://...时确认 TOS URI、base model 和名称；用户还没有 TOS URI 时先引导开通/上传 TOS，不要直接跑upload - 用户要改名 / 改描述：读
references/arkcli-custommodel-update.md，确认意图后用update - 用户要删除：读
references/arkcli-custommodel-delete.md，先查active_endpoints，确认后再执行 - 用户要量化：先读
references/arkcli-custommodel-available-quantizations.md，再读references/arkcli-custommodel-quantize.md
列表参数与输出契约
custommodel list --sort-order只接受小写asc/desc。收到其他值时应把它视为本地参数错误，不要尝试调用接口或改成其他大小写后盲目重试。- 使用
--format table或--format csv时，每个result.items[]模型是一行；不要把分页响应根对象或resultmap 当成模型记录。需要保留完整分页元数据时使用 JSON/YAML。
部署前的自定义模型目标澄清
仅当用户的最终目标是“把我的自定义模型部署成 Endpoint”、但没有给出唯一 cm-* 时执行本节；用户已明确给出 cm-* 时跳过。
- 先执行同范围只读查询：
arkcli models custommodel list --mine --statuses ready --page-all --page-delay 500 --format json。保留退出码与 stderr，不能把认证、权限或网络失败当作空清单；认证/权限错误按 shared 处理，不扫描凭证或自动切身份。 - 候选只能来自本轮完整结构化结果。输出被宿主截断时，先读取工具保存的完整文件；确实没有完整捕获时，允许把同一只读查询的 stdout 重新落盘，stderr 单独保留，再用
jq/sed检查result.items与分页信息。该同范围补查一轮最多执行一次，不循环重试。jq空结果或字段缺失时先核对当前 reference 与原始 JSON，不盲猜字段、不凭记忆补cm-*。分页未取全、补查仍失败或关键字段仍缺失时，说明具体边界并停止；拿全候选前不出选择题，更不执行部署。 - 按 0 / 1 / N 收敛：
- 0 个：停止，提示用户先 upload、量化或完成精调产物导出。
- 1 个：复述该模型的
id / name / foundation_model / create_time，将它作为唯一目标转交arkcli-deploy。 - N 个：使用宿主提供的结构化选择能力，把每个候选的
id / name / foundation_model / create_time直接列给用户选择；不要在通用 Skill 中写死某个宿主的工具名，也不要额外写死Other选项。
- 唯一目标确定前，不执行
arkcli +deploy、arkcli infer endpoint create或 Raw API。目标选择完成后转arkcli-deploy，并继续遵守其写操作确认；选择模型本身不等于授权部署。
Show full SKILL.md (279 more words)Show less
Agent 快速执行顺序
- 不确定认证状态时，先
arkcli auth status - "我的自定义模型"语义：直接
custommodel list --mine，不要套 shared 的 Tags 默认过滤（custommodel 服务端原生支持--mine） - 上传前必填三项：
--name/--base-model <foundation-model-id>/--tos tos://<bucket>/<prefix>；缺任一会被服务端拒 upload/quantize是异步任务：返回后用custommodel get <id>轮询 status，不要原地循环 upload/quantizequantize前必跑available-quantizations <id>：不同 base model 支持的量化模式不同，盲传服务端会拒；若用户关心 token / 模型单元等部署形态，优先看返回里的supported_inference_types_by_quantizationquantize --dry-run只输出本地preview.v1，不会调用CreateQuantizedCustomModel；steps[].payload只描述真实请求字段，不应出现后端DryRun。它不是服务端校验，核对后仍需确认再执行真实量化delete/update/quantize是写操作，执行前向用户复述影响范围delete默认会走 [Y/N] 二次确认；--yes表示跳过本地二确，--dry-run表示只预览不删除。只有用户已经明确确认删除目标和影响范围后，agent 才能把--yes加到命令里get --transform是custommodel get自己的字段白名单，不是全局 GJSON 表达式；要查嵌套路径时不要把它当作全局--transform
典型业务链路
1. 从 TOS 上传新自定义模型
auth status → custommodel upload --name X --base-model <fm-id> --tos tos://b/p
→ custommodel get <id> （轮询直到 status=ready）
→ custommodel get <id> --transform 'artifact_types' （看产物形态）2. 量化已就绪的自定义模型
custommodel get <id> （确认 status=ready）
→ custommodel available-quantizations <id> （看支持哪些 mode）
→ custommodel quantize <id> --quantization <mode> --dry-run
→ 用户确认量化目标和影响范围
→ custommodel quantize <id> --quantization <mode>
→ custommodel get <new-id> （量化结果是新 cm-xxxxx，再次轮询）3. 准备给 +deploy 当目标
custommodel list --mine --statuses ready --page-all --page-delay 500 --format json
→ 按 0 / 1 / N 澄清唯一 cm-xxxxx
→ +deploy --model cm-xxxxx ... （若已有 Running Endpoint 会复用；详见 ../arkcli-deploy/SKILL.md）4. 清理不再使用的自定义模型
custommodel get <id> --transform 'active_endpoints' （确认无 endpoint 引用）
→ custommodel delete <id> --dry-run
→ custommodel delete <id> （交互二确）或 custommodel delete <id> --yes反模式（agent 必读）
- 不要用
arkcli models search/list找自定义模型 —— 那两条只走 FoundationModel 目录，自传模型一律不在里面。要找自传模型用custommodel list --search <kw>或--mine - 不要在
upload之后立刻quantize—— upload 是异步任务，status 经历preparation → processing → ready；先custommodel get <id>确认 ready，再走available-quantizations→quantize - 不要给
quantize传一个available-quantizations没列的 mode —— 不同 base model 支持的量化集合不同，盲传必失败。先available-quantizations <id>，从返回里挑 - 不要把
cm-xxxxx直接传给+chat/+gen的--model—— 自定义模型必须先通过+deploy获得 endpoint（ep-xxx）才能推理调用；+deploy可能复用已有 Running Endpoint - 不要在多个 ready 自定义模型中自行挑一个部署 —— 先按“部署前的自定义模型目标澄清”让用户从本轮实时结果中选择
- 不要为了自动化主动补
--yes—— 没--yes时 CLI 会走 [Y/N] 二确；只有用户已经确认删除cm-xxxxx且知道 endpoint 引用风险时才带 - 不要在 "我的" 语义下走 shared 的 Tags 客户端过滤 ——
custommodel list --mine是服务端原生过滤，更准也更省请求 - 不要密集刷
get来轮询 status —— 推荐间隔 ≥ 10s，否则会被限流
命令一览
| 命令 | 说明 |
|---|---|
arkcli models custommodel list | 翻页 + 多维过滤 |
arkcli models custommodel get <id> | 详情 / 轮询 status |
arkcli models custommodel upload | 从 TOS 导入（异步） |
arkcli models custommodel update <id> | 改名 / 改描述 |
arkcli models custommodel delete <id> [--yes] [--dry-run] | 删除（破坏性，不可逆）；默认二确，--yes 跳过，--dry-run 预览 |
arkcli models custommodel available-quantizations <id> | 查可用量化模式（quantize 前必跑） |
arkcli models custommodel quantize <id> --quantization <mode> [--dry-run] | 量化（异步）；--dry-run 仅本地预览，不调用后端 |
常见降级
- 认证失败：转
../arkcli-auth/SKILL.md - profile / region 看起来不对：转
../arkcli-config/SKILL.md - 找的是基础模型不是自定义模型：转
../arkcli-models/SKILL.md - 拿到自定义模型后要部署：转
../arkcli-deploy/SKILL.md - 产品命令未覆盖（例如想直接触发 customization job）：转
../arkcli-api-explorer/SKILL.md
参考
references/arkcli-custommodel-list.mdreferences/arkcli-custommodel-get.mdreferences/arkcli-custommodel-upload.mdreferences/arkcli-custommodel-update.mdreferences/arkcli-custommodel-delete.mdreferences/arkcli-custommodel-available-quantizations.mdreferences/arkcli-custommodel-quantize.mdreferences/evals.md- arkcli-models — 基础模型查询（与本 skill 是两套资源）
- arkcli-deploy — 拿到 ready 的自定义模型后部署成 endpoint
- arkcli-shared — 认证、全局 flag、安全规则
© volcengine, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 8 other files (references) in skills/arkcli-custommodel of volcengine/ark-cli.
- SKILL.md
- references/arkcli-custommodel-available-quantizations.md
- references/arkcli-custommodel-delete.md
- references/arkcli-custommodel-get.md
- references/arkcli-custommodel-list.md
- references/arkcli-custommodel-quantize.md
- references/arkcli-custommodel-update.md
- references/arkcli-custommodel-upload.md
- references/evals.md
Open the folder on GitHubat commit fb5b7be
Compare with similar skills
Arkcli Custommodel next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Arkcli Custommodel this skillvolcengine/ark-cli | 140 | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Guizang Social Cardsop7418/guizang-social-card-skill | 7.4k | 1 repos | ~7.8k | Automated safety check: Pass | AGPL-3.0 | |
| Weekly Changelog Videoheygen-com/hyperframes | 59k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | |
| Anthropic Brand Stylinganthropics/skills | 180k | 30 repos | ~559 | Automated safety check: Pass | Apache-2.0 | |
| Native Subtitle Quote Imagechengyi-ai/native-subtitle-quote-image | 2.2k | 2 repos | ~1.8k | Automated safety check: Pass | MIT | |
| MoneyPrinterTurbo Video Generatorharry0703/MoneyPrinterTurbo | 129k | — | ~2.1k | Automated safety check: Warn | MIT |
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Questions about Arkcli Custommodel
What does Arkcli Custommodel do?
arkcli 自定义模型仓库管理：从 TOS 导入自定义模型、查询/筛选自定义模型、查看详情、改名、删除、查询可用量化模式、量化已就绪的模型。任何提到自定义模型 ID（cm-）的管理、部署准备，或要求用 cm- 直接对话/推理/试效果的边界判断，都必须使用本 skill。注意：查询火山公共基础模型（doubao 等 foundation models）走 arkcli-models；本…. Arkcli Custommodel is an agent skill from volcengine/ark-cli.
When should I use Arkcli Custommodel?
Arkcli Custommodel fits situations like: media & Creative work in your project.
How do I install Arkcli Custommodel in Claude Code?
Run `npx skills add volcengine/ark-cli --skill arkcli-custommodel -a claude-code`. Or copy the skill folder (skills/arkcli-custommodel in volcengine/ark-cli) into .claude/skills/arkcli-custommodel in your project. Claude Code loads it when a task matches its description.
How do I install Arkcli Custommodel in Codex?
Run `npx skills add volcengine/ark-cli --skill arkcli-custommodel -a codex`. Or copy the skill folder (skills/arkcli-custommodel in volcengine/ark-cli) into .agents/skills/arkcli-custommodel in your project. Codex loads it when a task matches its description.
Can I use Arkcli Custommodel in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add volcengine/ark-cli --skill arkcli-custommodel -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/arkcli-custommodel, .gemini/skills/arkcli-custommodel, .github/skills/arkcli-custommodel and .opencode/skills/arkcli-custommodel in your project.
What does Arkcli Custommodel need to run?
SKILL.md names no scripts, command-line tools or credentials: Arkcli Custommodel is instructions for the agent only.
Does Arkcli Custommodel access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Arkcli Custommodel safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Arkcli Custommodel use?
Arkcli Custommodel is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Arkcli Custommodel use?
About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.8k tokens, read only when the agent opens those files.
What are the alternatives to Arkcli Custommodel?
Skills that share tags, products or a category with Arkcli Custommodel: Guizang Social Cards (op7418/guizang-social-card-skill, 7.4k stars), Weekly Changelog Video (heygen-com/hyperframes, 59k stars), Anthropic Brand Styling (anthropics/skills, 180k stars) and Native Subtitle Quote Image (chengyi-ai/native-subtitle-quote-image, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Arkcli Custommodel?
volcengine (a GitHub organization) maintains it in volcengine/ark-cli, which has 140 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on September 29, 2026.
Source: volcengine/ark-cli on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.