Token导航 LogoToken导航

Agent Skill · 研究检索

byted-airesearch-videoeval(byted airsearch 视频评估)

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

byted-airesearch-videoeval 是研究检索类 Agent Skill,可用宿主为 Local Agent,通过unknown获取,权限为接触敏感数据;许可证信息还不明确,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 38,727。

总安装 1,518周安装 62下载 486核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:byted-airesearch-videoeval(byted airsearch 视频评估)
来源仓库:https://skills.volces.com
仓库路径:byted-airesearch-videoeval
安装命令:
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。当前暂无明确安装命令,请以来源页面说明为准。

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

byted-airesearch-videoeval 用于辅助视频生成、动画合成和 Remotion 项目开发。它支持镜头组织、素材说明生成和渲染问题排查。使用时需确认分辨率、时长、素材路径和导出格式等参数。涉及人物肖像或商业发布时,应先核对版权授权和内容审核要求。建议在非生产环境充分测试后再用于正式项目。

来源仓库内路径:byted-airesearch-videoeval

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Local Agent;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    没有现成安装命令,按unknown的说明从来源页面获取,仓库路径是 byted-airesearch-videoeval。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

byted-airesearch-videoeval 怎么安装?

公开资料没有给出可以直接复制的命令,需要按来源页面说明手动安装,仓库内路径为 byted-airesearch-videoeval。

byted-airesearch-videoeval 支持哪些 AI 工具?

公开资料标注支持 Local Agent。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

byted-airesearch-videoeval 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

byted-airesearch-videoeval 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

byted-airesearch-videoeval 用的人多吗?

公开数据是累计安装 1,518 次,近一周安装 62 次,下载 486 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

byted-airesearch-videoeval 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 Local Agent 一种宿主,触发方式和使用习惯不用来回切换。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Local Agent,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
byted-airesearch-videoeval

byted airsearch 视频评估 · 本页

1,518—接触敏感数据未明确未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Byted Airesearch Videoeval

Use this skill to submit and query long-running material evaluation tasks.

When to use

Use this skill when the user wants to:

  • evaluate a video material or creative asset
  • submit a material evaluation task and get back a task identifier
  • check the status of an existing evaluation task later
  • fetch the final detail/result of a previously created evaluation task

Do not use this skill for generic video upload requests.

Current workflow

  1. Validate the full input batch before any upload starts.
  2. Upload the local video files and capture the returned attachment_id values.
  3. Create a task with the uploaded attachment IDs.
  4. Return success immediately after the task is created.
  5. Ask the user to query task list or task detail later if they want progress or results.

This workflow is intentionally non-blocking. Do not poll automatically after task creation.

Mandatory behavior

  • Do not expose the upload API as a standalone user-facing capability.
  • Do not trigger this skill for generic requests such as “upload this video”, “store this file”, or “send this video”.
  • Only call the upload API when the user explicitly intends to create a new material evaluation task.
  • For new task creation, prefer scripts/submit_evaluation_task.py so validation, upload, and task creation stay in one controlled flow.
  • Treat scripts/upload_video.py as an internal helper used by the orchestration flow, not as the primary user entrypoint. The script itself rejects direct use unless it is called with the internal orchestration marker.

For multi-file submissions, use the orchestration entrypoint so the whole batch is validated before the first upload starts.

Submission limits

  • A single task can include at most 10 videos.
  • Non-enabled users have a rolling free quota of at most 10 submitted videos within the last 24 hours.
  • The new task's video count is added to the number of videos already submitted in the last 24 hours. If the total exceeds 10, the service rejects the task and asks the user to contact Volcengine sales to enable access.
  • Enabled users are not restricted by this rolling 24-hour free quota.
  • Quota accounting is based on the actual number of videos submitted per task, with no deduplication.
  • Any task created within the last 24 hours counts toward the rolling quota, including running tasks.
  • Login-based access and API key access share the same quota pool.
  • The skill enforces the per-task limit locally before upload starts. The rolling 24-hour quota is enforced by the service, and the skill should surface the service rejection with a clear explanation.

Authentication

The current APIs use API key authentication.

All API requests sent by this skill must include the header:

  • x-product-version: 20
  • Authorization: bearer {API_KEY}

Preferred input methods:

  • --api-key "<api-key>"
  • BYTED_AIRESEARCH_VIDEOEVAL_API_KEY

If no API key is available, ask the user to create or view one at:

  • https://console.volcengine.com/datatester/ai-research/audience/list?tab=apikey

Then ask the user to provide the API key before calling the API.

If the API key is missing, the scripts must fail immediately with a clear error that points the user to the API key page above.

Known API coverage

Upload attachment

  • Endpoint: POST https://console.volcengine.com/datatester/compass/api/v3/survey/attachment
  • Request: multipart/form-data
  • File field: file
  • Upload constraints:

- each upload request contains exactly one video file - each video must be 50MB or smaller - file format must be mp4 - MIME type must be video/mp4

  • Output mapping:

- preserve the raw attachment payload - map the attachment object's id field to attachment_id

The upload_video.py script is an internal helper for the create-task workflow. It is not the primary user-facing entrypoint.

Create task

  • Endpoint: POST https://console.volcengine.com/datatester/compass/api/v3/survey/task
  • Fixed request fields:

- form_id: 0 - agent_id: 125 - audience_id: 3664529

  • Optional request fields currently exposed:

- prompt - language - is_typical_user_enabled - typical_user_count - typical_user_selection_mode - is_report_enabled - attachment_ids

  • Create constraints:

- one task submission can include at most 10 videos - attachment_ids must contain at most 10 items per request

The create step should send the uploaded attachment_id as a one-element attachment_ids array unless multiple attachment IDs are explicitly provided.

List and detail

Task detail is wired and can query an existing task directly:

  • Endpoint: GET https://console.volcengine.com/datatester/compass/api/v3/survey/task/{id}
  • Current auth: API key bearer token
  • Output mapping:

- map the task object's id field to task_id - map the task object's status field to task_status - parse task.detail - keep only items where key == video_structured_result and sub_tab!= null - expose a compact summary block for downstream agent use

Task list is wired and can query existing tasks directly:

  • Endpoint: GET https://console.volcengine.com/datatester/compass/api/v3/survey/task
  • Current auth: API key bearer token
  • Current fixed query params:

- page=1 - page_size=100 - agent_id=125

  • Output mapping:

- map each task item to task_id, name, status, created_at, updated_at - preserve pagination info in data.page

Commands

# Validate a whole batch before upload, then upload all files and create the task
python scripts/submit_evaluation_task.py \
  --file /path/to/video-1.mp4 \
  --file /path/to/video-2.mp4 \
  --api-key "<api-key>"

# Single-video create flow
python scripts/submit_evaluation_task.py \
  --file /path/to/video.mp4 \
  --prompt "Evaluate this material for audience fit and content quality." \
  --api-key "<api-key>"

# Query task list later
python scripts/list_evaluation_tasks.py

# Query task detail later
python scripts/get_evaluation_task_detail.py --task-id 12345

Response handling

All scripts emit JSON to stdout with the same top-level envelope:

  • status
  • message
  • request_id
  • data
  • error

Important normalized fields:

  • submit task: data.task_id, data.task_status, data.submitted_video_count
  • list: data.items
  • detail: data.detail, data.summary

Final answer rules

  • Use the structured JSON returned by the detail endpoint as the internal source of truth.
  • Present the final answer in human-readable natural language.
  • When the task is finished, prefer a concise report-style answer rather than a raw data dump.
  • Do not dump raw JSON to the user.
  • Do not expose internal field names such as video_eval, video_user_report, distribution, field_desc, or similar implementation-oriented keys.
  • Apply the same rule to task list responses: use the list result as internal source data, but present the outcome as a natural-language summary rather than raw fields.
  • For task list answers, it is acceptable to include the task ID, task name, status, created time, and updated time in human-readable prose, because those fields help the user choose a task for follow-up detail queries.
  • When multiple videos are present, summarize them separately.
  • For finished task detail results, prefer a readable report flow such as: task conclusion first, then one short section per video, then overall recommendations if the source data supports them.
  • If the task is not finished yet, do not fabricate a report. Clearly state the current status and ask the user to check again later.
  • Only provide raw structured data if the user explicitly asks for the raw result.

Practical guidance

  • For new submissions, use the orchestration flow rather than exposing upload as a standalone step to the user.
  • Validate the local file before upload. Reject non-MP4 files, files with non-video/mp4 MIME types, or files larger than 50MB with a direct and actionable error message.
  • Validate the task creation input before calling the API. Reject any request that contains more than 10 attachment IDs with a direct and actionable error message.
  • For a multi-video submit flow, validate the full batch size before any upload starts. If the batch contains more than 10 files, fail immediately and do not upload anything.
  • If the service rejects task creation because the rolling 24-hour free quota was exceeded, use this standard Chinese wording for the user-facing message: 免费版用户每24小时最多提交10个评估视频,如需购买请联系火山引擎销售人员
  • After create succeeds, tell the user the task has been submitted successfully and can be checked later.
  • Use task list when the user wants to browse or find historical tasks.
  • Use task detail when the user already knows the task ID and wants the final result.

平台分布

Local Agent

76.19%
按下载量换算370

安全审计

暂无安全审计结果可展示。

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills