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humehume 搜索

Agent Skill

hume 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

总安装

475

周安装

20

GitHub Stars

56

下载量

166
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:hume(hume 搜索)
来源仓库:https://github.com/vm0-ai/vm0-skills
仓库路径:skills/hume
安装命令:
npx skills add https://github.com/vm0-ai/vm0-skills --skill hume
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/vm0-ai/vm0-skills --skill hume

简介

hume 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 安装前需确认权限范围和维护状态,注意是否会触发联网、命令执行或文件读写。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

Troubleshooting

If requests fail, run zero doctor check-connector --env-name HUME_TOKEN or zero doctor check-connector --url https://api.hume.ai/v0/batch/jobs --method GET

Expression Measurement (Batch)

Start Inference Job from URLs

Write to /tmp/hume_request.json:

{
  "urls": ["https://example.com/media-file.mp4"],
  "models": {
    "face": {},
    "prosody": {},
    "language": {}
  },
  "notify": true
}

Then run:

curl -s -X POST "https://api.hume.ai/v0/batch/jobs" --header "Content-Type: application/json" --header "X-Hume-Api-Key: $HUME_TOKEN" -d @/tmp/hume_request.json | jq .

Start Inference Job with Text

Write to /tmp/hume_request.json:

{
  "text": ["I am so excited about this!", "This is really disappointing."],
  "models": {
    "language": {}
  }
}

Then run:

curl -s -X POST "https://api.hume.ai/v0/batch/jobs" --header "Content-Type: application/json" --header "X-Hume-Api-Key: $HUME_TOKEN" -d @/tmp/hume_request.json | jq .

List Jobs

curl -s "https://api.hume.ai/v0/batch/jobs?limit=10" --header "X-Hume-Api-Key: $HUME_TOKEN" | jq .

List Jobs by Status

curl -s "https://api.hume.ai/v0/batch/jobs?limit=10&status=COMPLETED" --header "X-Hume-Api-Key: $HUME_TOKEN" | jq .

Get Job Details

curl -s "https://api.hume.ai/v0/batch/jobs/{job-id}" --header "X-Hume-Api-Key: $HUME_TOKEN" | jq .

Get Job Predictions

curl -s "https://api.hume.ai/v0/batch/jobs/{job-id}/predictions" --header "X-Hume-Api-Key: $HUME_TOKEN" | jq .

Download Job Artifacts

curl -s "https://api.hume.ai/v0/batch/jobs/{job-id}/artifacts" --header "X-Hume-Api-Key: $HUME_TOKEN" --output /tmp/hume_artifacts.zip

Text-to-Speech

Synthesize Speech (JSON Response)

Write to /tmp/hume_request.json:

{
  "utterances": [
    {
      "text": "Hello, how are you today?",
      "description": "A warm and friendly greeting"
    }
  ],
  "format": {
    "type": "mp3"
  }
}

Then run:

curl -s -X POST "https://api.hume.ai/v0/tts" --header "Content-Type: application/json" --header "X-Hume-Api-Key: $HUME_TOKEN" -d @/tmp/hume_request.json | jq .

The response contains base64-encoded audio in .generations[].audio.

Synthesize Speech with Specific Voice

Write to /tmp/hume_request.json:

{
  "utterances": [
    {
      "text": "Welcome to our platform!",
      "speed": 1.0
    }
  ],
  "voice": {
    "name": "{voice-name}"
  },
  "format": {
    "type": "mp3"
  }
}

Then run:

curl -s -X POST "https://api.hume.ai/v0/tts" --header "Content-Type: application/json" --header "X-Hume-Api-Key: $HUME_TOKEN" -d @/tmp/hume_request.json | jq .

Synthesize and Save Audio File

Write to /tmp/hume_request.json:

{
  "utterances": [
    {
      "text": "This is a test of text-to-speech synthesis."
    }
  ],
  "format": {
    "type": "mp3"
  }
}

Then extract and decode the audio:

curl -s -X POST "https://api.hume.ai/v0/tts" --header "Content-Type: application/json" --header "X-Hume-Api-Key: $HUME_TOKEN" -d @/tmp/hume_request.json | jq -r '.generations[0].audio' | base64 -d > /tmp/hume_output.mp3

Synthesize Multiple Utterances

Write to /tmp/hume_request.json:

{
  "utterances": [
    {
      "text": "First sentence.",
      "description": "calm and measured"
    },
    {
      "text": "Second sentence!",
      "description": "excited and energetic",
      "trailing_silence": 0.5
    }
  ],
  "format": {
    "type": "mp3"
  }
}

Then run:

curl -s -X POST "https://api.hume.ai/v0/tts" --header "Content-Type: application/json" --header "X-Hume-Api-Key: $HUME_TOKEN" -d @/tmp/hume_request.json | jq .

EVI Configs

List Configs

curl -s "https://api.hume.ai/v0/evi/configs?page_size=20" --header "X-Hume-Api-Key: $HUME_TOKEN" | jq .

Create Config

Write to /tmp/hume_request.json:

{
  "name": "My EVI Config"
}

Then run:

curl -s -X POST "https://api.hume.ai/v0/evi/configs" --header "Content-Type: application/json" --header "X-Hume-Api-Key: $HUME_TOKEN" -d @/tmp/hume_request.json | jq .

EVI Prompts

List Prompts

curl -s "https://api.hume.ai/v0/evi/prompts?page_size=20" --header "X-Hume-Api-Key: $HUME_TOKEN" | jq .

Create Prompt

Write to /tmp/hume_request.json:

{
  "name": "Customer Support Agent",
  "text": "You are a friendly and empathetic customer support agent. Listen carefully and help resolve issues."
}

Then run:

curl -s -X POST "https://api.hume.ai/v0/evi/prompts" --header "Content-Type: application/json" --header "X-Hume-Api-Key: $HUME_TOKEN" -d @/tmp/hume_request.json | jq .

EVI Chats

List Chat Events

curl -s "https://api.hume.ai/v0/evi/chats/{chat-id}?page_size=50&ascending_order=true" --header "X-Hume-Api-Key: $HUME_TOKEN" | jq .

Available Models for Expression Measurement

ModelDescription
faceFacial expression analysis from images/video
prosodyVocal expression analysis from audio
languageEmotion analysis from text
nerNamed entity recognition from text
burstNon-speech vocal sounds (laughter, sighs)
facemeshDetailed facial landmark detection

TTS Utterance Parameters

ParameterTypeDescription
textstringContent to convert to speech (required)
descriptionstringActing directions or voice style prompt
speednumberSpeech rate multiplier (default: 1.0)
trailing_silencenumberSilence after utterance in seconds (default: 0)

Response Codes

StatusDescription
200Success
201Resource created
400Invalid request parameters
401Missing or invalid API key
404Resource not found
429Rate limit exceeded
5xxServer error

Guidelines

  1. Authentication: Use X-Hume-Api-Key header (not Bearer token) for all requests
  2. Batch Jobs: Jobs are asynchronous; poll the job details endpoint until status is COMPLETED
  3. Models: Specify only the models you need in batch requests to reduce processing time
  4. TTS Description: Use the description field to control emotional tone and style of generated speech
  5. Pagination: EVI endpoints use zero-based page numbering with configurable page size (1-100)
  6. API Key Types: Organization API Key for TTS and EVI; Personal API Key for Expression Measurement

API Reference

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.52%
按下载量换算61

Claude

30.44%
按下载量换算51

Cursor

19.43%
按下载量换算32

Gemini CLI

9.3%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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