Agent Skills › OpenBMB/PilotDeck › meeting-recorder-assistant

meeting-recorder-assistant

GitHub

智能会议助手，支持录音、语音转文字及说话人分离。自动生成结构化会议纪要，提取行动项与任务分配，并进行情感分析。适用于需要记录会议、转录音频或分析会议内容的场景。

skills/meeting-recorder-assistant/SKILL.md OpenBMB/PilotDeck

触发场景

用户需要录制会议音频用户要求将语音转换为文本用户请求生成会议纪要用户需要从对话中提取行动项或任务用户希望分析会议的情感倾向

安装

npx skills add OpenBMB/PilotDeck --skill meeting-recorder-assistant -g -y

更多选项

不安装直接使用

npx skills use OpenBMB/PilotDeck@meeting-recorder-assistant

指定 Agent (Claude Code)

npx skills add OpenBMB/PilotDeck --skill meeting-recorder-assistant -a claude-code -g -y

安装 repo 全部 skill

npx skills add OpenBMB/PilotDeck --all -g -y

预览 repo 内 skill

npx skills add OpenBMB/PilotDeck --list

SKILL.md

Frontmatter

{
    "name": "meeting-recorder-assistant",
    "description": "Intelligent meeting recording and transcription assistant with automated minutes generation, action item extraction, and sentiment analysis. Supports audio transcription, speaker diarization, meeting summarization, and task extraction. Use when users need to record meetings, transcribe audio, generate meeting minutes, extract action items, or analyze meeting content."
}

Meeting Recorder Assistant

An intelligent meeting assistant that records, transcribes, and analyzes meetings to generate actionable insights.

Features

Audio Recording: Record meeting audio with timestamps
Speech-to-Text: Transcribe audio to text with speaker identification
Meeting Minutes: Auto-generate structured meeting summaries
Action Items: Extract tasks and assignments from discussions
Sentiment Analysis: Analyze meeting tone and engagement

Usage

Record and Transcribe

from scripts.meeting_recorder import MeetingRecorder

# Initialize recorder
recorder = MeetingRecorder()

# Start recording
recorder.start_recording("/tmp/meeting_audio.wav")

# Stop and transcribe
transcript = recorder.stop_and_transcribe()
print(f"Transcript: {transcript['text']}")

Generate Meeting Minutes

from scripts.meeting_minutes import generate_minutes

# Generate structured minutes
minutes = generate_minutes(transcript_path="/tmp/transcript.json")
print(f"Summary: {minutes['summary']}")
print(f"Action Items: {minutes['action_items']}")

Extract Action Items

from scripts.action_extractor import extract_actions

# Extract tasks from transcript
actions = extract_actions("/tmp/transcript.txt")
for action in actions:
    print(f"- {action['task']} (Assigned: {action['assignee']})")