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Agent Skill · 开发

trio-vision(三人视觉)

trio-vision 用于处理图像、截图、视觉识别或图片素材相关工作,适合在 OpenClaw 中需要让 Agent 分析图片、整理视觉素材或辅助图像流程时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

trio-vision 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 4,759。

总安装 7,584周安装 316GitHub Stars 公开资料未说明下载 2,528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。
GitHub
许可证
MIT-0
版本
1.0.0

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:trio-vision(三人视觉)
来源仓库:https://github.com/drandrewlaw/trio-vision
安装命令:
openclaw skills install trio-vision
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。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install trio-vision

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于处理图像、截图和视觉识别相关任务,支持智能摄像头功能。适合在 OpenClaw 中需要让 Agent 分析图片、监控画面或处理视觉素材时使用。可将实时摄像头变为智能设备,用英语描述内容并在事件发生时发送警报。安装前建议核实权限、维护状态及是否触发图像分析或外部服务调用。

trio-vision 属于开发类 Skill,可作为该场景下的辅助能力补充。

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 OpenClaw;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

    可以直接复制的命令是 openclaw skills install trio-vision;命令里的占位符换成自己的路径或密钥再执行。

  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

trio-vision 怎么安装?

在终端执行 openclaw skills install trio-vision。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

trio-vision 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

trio-vision 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。

trio-vision 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

trio-vision 用的人多吗?

公开数据是累计安装 7,584 次,近一周安装 316 次,下载 2,528 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。

trio-vision 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、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。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
trio-vision

三人视觉 · 本页

7,584—接触敏感数据MIT-0有提醒

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

name
trio-vision
description
Turn any live camera into a smart camera — describe what to watch for in plain English, get alerts in your chat when it happens. Ask questions about any live stream (YouTube, Twitch, security cameras, RTSP), set up continuous monitoring with custom conditions, or get periodic summaries of what's happening. No ML expertise required.
homepage
https://docs.machinefi.com
license
Apache-2.0
metadata
{"openclaw":{"emoji":"📹","requires":{"env":["TRIO_API_KEY"],"anyBins":["curl","python3"]},"primaryEnv":"TRIO_API_KEY"}}

Trio Vision — Turn Any Camera Into a Smart Camera

Stop getting dumb motion alerts for every shadow. Describe what actually matters in plain English — get notified only when it happens, right in your chat. Powered by Trio by MachineFi.

When to Use

  • User asks what's happening on a camera, stream, or video feed ("is anyone at my front door?")
  • User wants smart alerts for specific events ("tell me when a package is delivered", "alert me if my dog gets on the couch")
  • User wants to monitor something they can't watch themselves (construction site, parking spot, warehouse)
  • User wants periodic summaries of a live feed ("summarize this stream every 10 minutes")
  • User provides any live stream URL: YouTube Live, Twitch, RTSP/RTSPS cameras, HLS streams

Prerequisites

  • A Trio API key. Get one free (100 credits) at https://console.machinefi.com
  • Set the key: export TRIO_API_KEY=your_key_here
  • Base URL: https://trio.machinefi.com/api

Available Actions

1. Check Once (Quick Snapshot)

Ask a yes/no question about what's currently visible on a stream. Costs 1 credit ($0.01).

curl -s -X POST "https://trio.machinefi.com/api/check-once" \
  -H "Authorization: Bearer $TRIO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "stream_url": "STREAM_URL_HERE",
    "condition": "NATURAL_LANGUAGE_CONDITION_HERE"
  }' | python3 -m json.tool

Optional parameters:

  • "include_frame": true — returns the analyzed frame as base64 image
  • "input_mode": "clip" — analyze a short video clip instead of a single frame (better for motion detection)
  • "clip_duration_seconds": 5 — clip length (1-10 seconds, only with clip/hybrid mode)

Response fields:

  • triggered (boolean) — whether the condition matched
  • explanation (string) — VLM's reasoning about what it sees
  • latency_ms — processing time in milliseconds

Input mode guidance:

  • Use "frames" (default) for static objects: "Is there a car in the driveway?", "Is the door open?"
  • Use "clip" for motion/actions: "Is someone walking?", "Did a package get delivered?"
  • Use "hybrid" for maximum accuracy (costs more)

2. Live Monitor (Continuous Event Detection)

Monitor a stream continuously and get alerted when a condition becomes true. Costs 2 credits/min ($0.02/min).

curl -s -X POST "https://trio.machinefi.com/api/live-monitor" \
  -H "Authorization: Bearer $TRIO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "stream_url": "STREAM_URL_HERE",
    "condition": "NATURAL_LANGUAGE_CONDITION_HERE",
    "interval_seconds": 10,
    "monitor_duration_seconds": 600,
    "max_triggers": 1
  }' | python3 -m json.tool

Optional parameters:

  • "webhook_url": "https://your-server.com/webhook" — receive HTTP POST notifications on trigger
  • "interval_seconds": 10 — check frequency (5-300 seconds)
  • "monitor_duration_seconds": 600 — how long to monitor (min 5 seconds)
  • "trigger_cooldown_seconds": 60 — minimum seconds between triggers
  • "max_triggers": null — set to null for unlimited triggers
  • "input_mode": "clip" — default for live-monitor, good for motion

Response: Returns a job_id. Use it to check status or cancel.

Delivery modes (automatic based on request):

  • If webhook_url is set → events POST to your webhook
  • If Accept: text/event-stream header is set (no webhook) → SSE stream
  • Otherwise → poll with GET /jobs/{job_id}

3. Live Digest (Periodic Summaries)

Get narrative summaries of what's happening on a stream at regular intervals. Costs 2 credits/min ($0.02/min).

curl -s -X POST "https://trio.machinefi.com/api/live-digest" \
  -H "Authorization: Bearer $TRIO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "stream_url": "STREAM_URL_HERE",
    "window_minutes": 10,
    "capture_interval_seconds": 60
  }' | python3 -m json.tool

Optional parameters:

  • "window_minutes": 10 — summary window length (1-60 minutes)
  • "capture_interval_seconds": 60 — frame capture frequency (10-300 seconds)
  • "webhook_url": "https://..." — receive summaries via webhook
  • "max_windows": 3 — number of summary windows before stopping
  • "include_frames": true — embed frames in summaries

Response: Returns a job_id.

4. Check Job Status

curl -s "https://trio.machinefi.com/api/jobs/JOB_ID_HERE" \
  -H "Authorization: Bearer $TRIO_API_KEY" | python3 -m json.tool

Job statuses: pending, running, stopped, completed, failed

5. List All Jobs

curl -s "https://trio.machinefi.com/api/jobs?limit=20&offset=0" \
  -H "Authorization: Bearer $TRIO_API_KEY" | python3 -m json.tool

Optional query params: status=running, type=live-monitor, limit=20, offset=0

6. Cancel a Job

curl -s -X DELETE "https://trio.machinefi.com/api/jobs/JOB_ID_HERE" \
  -H "Authorization: Bearer $TRIO_API_KEY" | python3 -m json.tool

Recommended Workflows

Quick Check Workflow

  1. Run check-once with the user's question and stream URL
  2. Report the triggered result and explanation to the user
  3. If the API returns an error about the stream, show the error and remediation

Monitoring Workflow

  1. Test the condition with check-once first to verify it works
  2. If the condition works, start live-monitor with appropriate settings
  3. Return the job_id and inform user how to check status or cancel
  4. If webhook_url is available, set it up for push notifications

Summary Workflow

  1. Start live-digest with the stream URL and appropriate window/interval
  2. Return the job_id so the user can check results later

Condition Writing Tips

  • Frame as binary yes/no questions: "Is there a person visible in the frame?"
  • Be specific: "Is there smoke rising from the building roof?" not "Is there smoke?"
  • One intent per condition — don't combine multiple checks
  • Use positive phrasing: "Are vehicles visible?" not "Is the parking lot not empty?"
  • Always test conditions with check-once before starting live-monitor

Error Handling

All errors return this structure:

{
  "error": {
    "code": "ERROR_CODE",
    "message": "Human-readable description",
    "remediation": "Actionable fix suggestion"
  }
}

Common error codes:

  • NOT_LIVESTREAM — URL is not a live stream. Confirm it's actively broadcasting.
  • STREAM_FETCH_FAILED — Cannot reach the stream. Check URL and network.
  • STREAM_OFFLINE — Stream exists but is offline. Wait for it to go live.
  • MAX_JOBS_REACHED — Too many concurrent jobs. Cancel old ones with DELETE /jobs/{id}.

If you get an error, always show the remediation field to the user — it contains actionable guidance.

Pricing Reference

ActionCost
Check once$0.01 / request
Live monitor$0.02 / minute
Live digest$0.02 / minute

Free tier: 100 credits ($1.00) on signup at https://console.machinefi.com

Rules

  • NEVER expose or log the $TRIO_API_KEY value in output shown to the user.
  • ALWAYS show the explanation field from check-once responses — it provides the VLM's reasoning.
  • ALWAYS test conditions with check-once before starting a live-monitor job.
  • When a user provides a stream URL, auto-detect whether they want a quick check, monitoring, or digest based on their intent.
  • For monitoring jobs, always return the job_id so the user can check status or cancel later.
  • If the API returns an error, show the error code and remediation to the user.
  • Inform users about credit costs before starting live-monitor or live-digest jobs (they charge per minute).

平台分布

OpenClaw

83.98%
按下载量换算2,123

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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