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Install in OpenClaw
/install meeting-record-analysis
Description
将会议录音转成结构化会议纪要。适用于用户上传会议音频后,希望通过 ASR 转写、LLM 总结和可选 TTS 播报,自动提取会议主题、讨论要点、决策和行动项的场景。输入支持 `audio_file`、`need_voice_summary`、`language`;默认输出 JSON 结构化纪要,并可附带语音摘要文件路径。
Usage Guidance
Before installing or running this skill: (1) Recognize that audio and transcript text are uploaded to external endpoints (models.audiozen.cn and api.senseaudio.cn by default). Only use with recordings you are comfortable sending off‑host. (2) The script expects API keys (LLM, ASR, TTS) via environment variables or .env files, but the registry metadata did not list these — confirm which secrets you'll provide and trust the service operators. (3) Inspect the .env.example and the script to confirm which env names and endpoints will be used; consider overriding endpoints to services you trust. (4) Run in an isolated environment (container) and review outputs/ for any sensitive intermediate files; remove credentials from working dirs when finished. (5) If you need higher assurance, ask the publisher for verified source/homepage and for the skill metadata to declare required env vars and endpoints explicitly.
Capability Analysis
Type: OpenClaw Skill
Name: meeting-record-analysis
Version: 1.0.0
The skill is a legitimate meeting minutes assistant designed to automate audio transcription, text cleaning, and summarization using external AI services (SenseAudio and AudioZen). The core logic in `scripts/run_meeting_minutes.py` follows a standard workflow: it transcribes audio via an ASR API, cleans the text using an LLM, and generates a structured summary in JSON format. The script uses well-known libraries like `openai` and `requests` and handles API keys through environment variables. No evidence of malicious intent, data exfiltration, or dangerous vulnerabilities was found; all network and file operations are directly aligned with the stated purpose of processing meeting recordings.
Capability Assessment
Purpose & Capability
The skill's name/description (convert meeting audio to structured minutes) aligns with the included script and prompts: it performs ASR, transcript cleaning, LLM summarization, and optional TTS. The code calls ASR, LLM and TTS endpoints (senseaudio.cn and models.audiozen.cn), which is coherent with the purpose.
Instruction Scope
SKILL.md and the script stay within the declared workflow (validate audio, call ASR, clean transcript, call LLM to produce JSON, optionally call TTS, save outputs). However, the instructions and code explicitly send audio and text to third‑party endpoints (https://api.senseaudio.cn and https://models.audiozen.cn), which means user data will be transmitted off‑host. The skill also attempts to load .env files from the skill dir or CWD for credentials.
Install Mechanism
No installer or remote download is used; it's an instruction+script package with a simple requirements.txt (openai, requests, python-dotenv). This is proportionate to the task and does not introduce high-risk remote installation behavior.
Credentials
The registry declares no required environment variables, but the script requires several API keys/env vars (MEETING_LLM_API_KEY or IME_MODEL_API_KEY, MEETING_ASR_API_KEY or SENSEAUDIO_API_KEY, MEETING_TTS_API_KEY or SENSEAUDIO_API_KEY, and optional overrides like MEETING_LLM_BASE_URL). The script will exit if required keys are missing and will load .env files from disk. Requiring multiple unrelated credentials without declaring them in metadata is a discrepancy and a potential surprise to users.
Persistence & Privilege
The skill is not always: true and does not request system-wide privileges. It writes outputs to a local outputs/ directory inside the skill, and may read .env files from the skill or current working directory. It does not modify other skills or system configs.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install meeting-record-analysis - After installation, invoke the skill by name or use
/meeting-record-analysis - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of AI Meeting Minutes Assistant.
- Converts meeting audio to structured minutes using ASR and LLM, with optional TTS voice summary.
- Inputs: `audio_file`, `need_voice_summary` (default: false), `language` (default: zh).
- Outputs structured JSON with topic, discussion_points, decisions, action_items, cleaned_transcript, and optional voice_summary_path.
- Includes cleaning of transcripts to remove filler words and repetitions, while preserving key facts and action items.
- Robust error handling for short audio, ASR failures, and overly long transcripts.
- Command line usage and API/workflow descriptions provided.
Metadata
Frequently Asked Questions
What is meeting record analysis?
将会议录音转成结构化会议纪要。适用于用户上传会议音频后,希望通过 ASR 转写、LLM 总结和可选 TTS 播报,自动提取会议主题、讨论要点、决策和行动项的场景。输入支持 `audio_file`、`need_voice_summary`、`language`;默认输出 JSON 结构化纪要,并可附带语音摘要文件路径。 It is an AI Agent Skill for Claude Code / OpenClaw, with 221 downloads so far.
How do I install meeting record analysis?
Run "/install meeting-record-analysis" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is meeting record analysis free?
Yes, meeting record analysis is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does meeting record analysis support?
meeting record analysis is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created meeting record analysis?
It is built and maintained by cows21 (@cows21); the current version is v1.0.0.
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