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

meeting-recorder-assistant

GitHub

智能会议助手，支持音频录制、语音转文字、说话人分离、会议纪要生成、行动项提取及情感分析。适用于会议录音、转录、总结和内容分析场景。

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

Trigger Scenarios

需要录制和转录会议音频自动生成结构化会议纪要从讨论中提取任务和行动项分析会议语气和参与度

Install

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

More Options

Use without installing

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']})")