SuperAPI AI Directory

arkcli-understand

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Updated 10-16 08:09

About this skill

arkcli +understand

CRITICAL — Before starting, MUST first use the Read tool to read ../arkcli-shared/SKILL.md, which contains the authentication gate, API Key error recovery, configuration troubleshooting, and command selection order. CRITICAL — Before executing +understand , MUST first use the Read tool to read references/arkcli-understand.md(commands/flags/return values/errors) and references/sub-skills.md(the purpose and expected output form of the 12 sub-skills). Do not assemble commands from memory.

Core Concepts

  • +understand Not 12 implementations, but 1 engine + a layer of semantics: the underlying engine is the data-plane Responses API used by +chat ; each sub-skill is just onerecipe {模态, fallback 模型, 内置 system prompt}. When the Platform Profile omits --model , the current Profile's Resources.Text.Default Endpoint must be used; only Plan-type Profiles use the recipe fallback model.
  • Command form:arkcli +understand <sub-skill> --input @file [prompt]。
    • args[0] Hits the registry(one of the 12) → treated as an explicit sub-skill, and the remaining positional arguments are treated as a prompt layered on top of the built-in prompt.
    • args[0] No hit → the entire positional argument string is treated as the prompt, and the server automatically routes by the file modality of thefirst --input automatic file modality routingto that modality's default sub-skill.
  • Must have --input: a sub-skill is "understanding a certain file"; without --input it will directly missing_input error out. A pure prompt cannot derive a recipe.
  • Return values are completely identical to +chat : arkcli flat schema {id, model, content, reasoning_content, usage},is not Responses native output[].content[].text nesting. See the "Return Values" section of references/arkcli-understand.md .
  • Multimodal upload: image/video/doc are automatically routed through the Files API by the SDK file:// preprocessor;audio is a special case—inlined as a base64 data URL,with a 25MB limit. See reference for details.
  • When the user temporarily provides --api-key / --base-url / Endpoint, MUST read ../arkcli-shared/references/execution-context.md. Do not guess the data plane/workflow based on the Key text or Endpoint name.
  • --dry-run Only resolves recipes locally, the default Endpoint already persisted in the current Profile, explicit models, and input references, and outputs a unified preview.v1; it does not read online Endpoint/model metadata, does not upload files, does not call the Responses API, does not generate model usage, and does not create a response id or persist responses. Values that can only be filled in online must be marked as unresolved, and the preview must not be treated as server-side validation.

Quick decision (understand vs chat vs gen)

User intent Which one to use
Hasexplicit output formmultimodal understanding tasks (transcription / translation / subtitles / box localization / GUI operation / field extraction / chapter-by-chapter summarization / multi-speaker / meeting minutes) +understand(hits a certain sub-skill)
Open-ended dialogue with images/videos, follow-up questions, reasoning, requiring multi-turn continuation (--store/--previous-response-id), requiring tools (web_search/function), or --text-format json_schema strict JSON ../arkcli-chat/SKILL.md
Generateimages / videos (not understanding existing assets) ../arkcli-gen/SKILL.md

One-sentence criterion:If the task maps to one of the sub-skill names below → use +understand; otherwise use +chatfor open-ended dialogue, and use +gen。

Agent quick execution order

  1. Determine which sub-skill the user's understanding task hits (see the table below). If it hits, explicitly include the sub-skill name; do not let it go through automatic routing to guess.
  2. The user only provides ep-... → arkcli resources resolve <ep-id> --format json; only when the user's task is a clear understanding output and supported_workflows contains understand, use this skill.
  3. The user provided a temporary Key/Base URL/Endpoint → decide the parameters according to the shared execution-context combination rules; do not switch profiles first.
  4. When there is no complete stateless context, pass the authentication gate: if the login state is uncertain, first arkcli auth status; for authentication failure, handle it according to ../arkcli-auth/references/auth-modes.md 's "Error recovery in API Key mode",do not retry in place。
  5. Prepare the input:--input @<file>(can be multiple times). For local files use the @ prefix; for remote use https:// / tos:// URL。
  6. By default do not pass --model: the Platform Profile will use the Resources.Text.Default already deployed in ep-xxx, consistent with +chat ; only Plan-type Profiles use the sub-skill's recipe fallback model. Pass the full versioned ID or ep-xxx。
  7. For segment-by-segment output add --stream; to fine-tune the task instruction use --system-prompt-append "...", or --system-prompt-override "..."。
  8. After running, return to the user's original goal; do not stop at intermediate artifacts.

sub-skill quick reference table (12 / 4 modalities)

The table below shows the recipe fallback models used by Plan-type Profiles. Platform Profiles do not use these bare model names, but instead use the current Profile's Resources.Text.Default Endpoint. If an override is truly needed, see the execution order above.

sub-skill Modality Plan recipe fallback model One-sentence purpose
image-caption image doubao-seed-1-6 Single-image/multi-image description, OCR (preserve the original text, do not paraphrase)
image-grounding image doubao-seed-1-6 Visual grounding: output the target bbox (x1,y1,x2,y2) + confidence
image-gui image doubao-seed-1-6 GUI screenshot → executable action sequence (JSON array of 12 action types)
doc-extract file doubao-seed-1-6 Extract structured JSON from PDFs/documents according to a schema (fill missing with null, preserve page)
video-summary video doubao-seed-1-6 Video summary: overall / segment / chapter + key timestamps
video-qa video doubao-seed-1-6 Video question answering: answer precisely by combining visuals + audio + timeline
vau video doubao-seed-2-0-lite Joint audio-video understanding: analyze the sound elements in the video and produce an audio analysis report
asr audio doubao-seed-2-0-lite Speech transcription: output plain text only, with no prefix/suffix/formatting whatsoever
asr-align audio doubao-seed-2-0-lite Subtitle timing: default SRT format (index + start/end time + text)
asr-speakers audio doubao-seed-2-0-lite Multi-speaker transcription: label [spk0] / [spk1] ...
ast audio doubao-seed-2-0-lite Speech translation: translate the speech in the audio into text
meeting-minutes audio doubao-seed-2-0-lite Meeting minutes: structured markdown (topic/participants/key points/decisions/follow-ups)

For the expected output form and example commands for each item, see references/sub-skills.md。

Automatic routing when the sub-skill is omitted

args[0] When it does not hit the registry, followthe first --input file extensioninfer the modality and fall back to that modality's default sub-skill:

Inferred modality Fallback sub-skill
image(.jpg/.png/.webp/...) image-caption
video(.mp4/.mov/...) video-qa
audio(.mp3/.wav/.m4a/...) asr
file (other extensions) doc-extract
  • Without --input , automatic routing is impossible(a recipe cannot be inferred from a pure prompt) → report missing_sub_skill。
  • Currentlyfallback is based only on file modality, with no prompt keyword-level routing(for example, saying "box out" will not automatically select image-grounding). If the Agent wants a non-default sub-skill (such as grounding / gui / summary / subtitles / translation), it shouldexplicitly write the sub-skill name, and not rely on automatic routing.

Command overview

Command Description
arkcli +understand image-caption --input @photo.jpg "描述这张图" Image description
arkcli +understand image-caption --input @doc.png "OCR,原样保留文字" OCR
arkcli +understand image-grounding --input @scene.jpg "框出所有红色car" Visual grounding bbox
arkcli +understand doc-extract --input @invoice.pdf "抽取 发票号/金额/日期" Document field extraction
arkcli +understand video-summary --input @clip.mp4 "按 chapter 总结" Video chapter-by-chapter summary
arkcli +understand video-qa --input @clip.mp4 "视频里出现了几辆车?" Video question answering
arkcli +understand asr --input @speech.mp3 Speech transcription (no prompt needed)
arkcli +understand asr-align --input @speech.mp3 Generate SRT subtitles
arkcli +understand asr-speakers --input @meeting.wav Multi-speaker transcription
arkcli +understand ast --input @speech.m4a "译成英文" Speech translation
arkcli +understand meeting-minutes --input @meeting.m4a Meeting minutes
arkcli +understand "<prompt>" --input @photo.jpg Omit sub-skill → automatically route by modality (here → image-caption)
arkcli +understand asr --input @speech.mp3 --stream Streaming segment-by-segment output
arkcli +understand image-caption --input @x.jpg --system-prompt-append "用英文回答" Append instructions after the built-in prompt
arkcli +understand image-caption --input @x.jpg "描述图片" --dry-run --format json Return the recipe / model / request summary preview.v1; zero network, no upload, no inference

Detailed documentation