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-usagenpx skills add volcengine/ark-cli --skill arkcli-usagegit 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 | $0.00242 | $0.04584 |
| Opus 5 | $0.00121 | $0.02292 |
| Sonnet 5 | $0.00048 | $0.00917 |
| Haiku 4.5 | $0.00024 | $0.00458 |
Grade A, and why
arkcli-usage 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 — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
arkcli usage
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 — usage stats 在执行之前,务必先用 Read 工具读取 references/arkcli-usage-stats.md,禁止直接盲目调用命令。
CRITICAL — usage plan 在执行之前,务必先用 Read 工具读取 references/arkcli-usage-plan.md,禁止直接盲目调用命令。
CRITICAL — usage plan-details 在执行之前,务必先用 Read 工具读取 references/arkcli-usage-plan-details.md,禁止直接盲目调用命令。
CRITICAL — usage balance 在执行之前,务必先用 Read 工具读取 references/arkcli-usage-balance.md,禁止直接盲目调用命令。
CRITICAL — usage seats 在执行之前,务必先用 Read 工具读取 references/arkcli-usage-seats.md,禁止直接盲目调用命令。
数据时效(务必先看):
usage stats走的是上游 BFF 的聚合管道,数据有 5–30 分钟延迟,定位为「日级 / 聚合分析」。 不要把它用于实时预算监控、限流、实时告警等需要秒级精度的控制场景——这类场景请直接读+chat/+gen等推理命令返回里的.usage字段(per-request、零延迟,详见 arkcli-chat 与 arkcli-gen)。
语音模型边界：TTS / ASR / 配音 / 朗读 / 播客 / 音色 / 实时语音交互，或
doubao-seed-tts-*/doubao-seed-asr-*/seedasr-*等广场语音模型，当前在 arkcli 只支持models search发现。不要用usage stats --model、usage plan-details或套餐/余额命令回答语音模型用量；直接说明 arkcli 不支持查询语音模型费用或用量。
stats / plan / plan-details / balance 区分:
stats出"按 token 计费的 inference 用量"(任何身份,5–30 分钟延迟)plan出"订阅套餐的 quota 快照"(AgentPlan / CodingPlan 个人版 + 团队版的"我用了几成 / 几号刷新")plan-details出"AgentPlan 按模型 / 套餐内外的时间序列调用明细"(AgentPlan 个人版 + 团队版,CodingPlan 没有按模型 endpoint)balance出"还剩多少 X"(余额视角,--type free-quota / media-asset / plan三选一)seats出"团队席位用量 admin 视角"(每个 seat 用了多少 / 套餐百分比;只是用量视图)。席位的列表 / 绑定 / 分配 / API Key 轮换 走arkcli-plans的plans team seat-list / seat-assign / rotate-apikey。用户问「我的套餐还剩多少额度」→
plan或balance --type plan(后者输出更精简);「我哪个模型用得最多」→plan-details;「我今天用了多少 token」→stats;「我还剩多少免费额度 / 媒资库容量」→balance;「每个 seat 用了多少 / 团队席位用量分布」→seats --with-usage(纯管理类:谁绑了哪个 seat / 列出席位 / 分配席位 / 轮换 key →arkcli-plans)。
What ships with it
5 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 · 147 lines · 242 tokens per session scan A b065a3afc79e
arkcli-usage is a skill published in the GitHub repository volcengine/ark-cli (112 stars, last pushed 5d ago), licensed Apache-2.0. It adds 242 tokens to every session and 4,584 once invoked, about $0.0012 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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