Skill: 0xfango/marswave-asr (version 0.1.0)

--- name: asr metadata: openclaw: emoji: "🎙️" requires: tools: ["coli"] description: | Transcribe audio files to text using local speech recognition. Triggers on: "转录", "transcribe", "语音转文字", "ASR", "识别音频", "把这段音频转成文字". --- ## When to Use - User wants to transcribe an audio file to text - User provides an audio file path and asks for transcription - User says "转录", "识别", "transcribe", "语音转文字" ## When NOT to Use - User wants to synthesize speech from text (use `/tts`) - User wants to create a podcast or explainer (use `/podcast` or `/explainer`) ## Purpose Transcribe audio files to text using `coli asr`, which runs fully offline via local speech recognition models. No API key required. Supports Chinese, English, Japanese, Korean, and Cantonese (sensevoice model) or English-only (whisper model). Run `coli asr --help` for current CLI options and supported flags. ## Hard Constraints - No shell scripts. Use direct commands only. - Always read config following `shared/config-pattern.md` before any interaction - Follow `shared/common-patterns.md` for interaction patterns - Never ask more than one question at a time <HARD-GATE> Use the AskUserQuestion tool for every multiple-choice step — do NOT print options as plain text. Ask one question at a time. Wait for the user's answer before proceeding. After all parameters are collected, summarize and ask the user to confirm before running any transcription. </HARD-GATE> ## Interaction Flow ### Step 0: Prerequisites Check Before config setup, silently check the environment: ```bash COLI_OK=$(which coli 2>/dev/null && echo yes || echo no) FFMPEG_OK=$(which ffmpeg 2>/dev/null && echo yes || echo no) MODELS_DIR="$HOME/.coli/models" MODELS_OK=$([ -d "$MODELS_DIR" ] && ls "$MODELS_DIR" | grep -q sherpa && echo yes || echo no) ``` | Issue | Action | |-------|--------| | `coli` not found | Block. Tell user to run `npm install -g @marswave/coli` first | | `ffmpeg` not found | Warn (WAV files still work). Suggest `brew install ffmpeg` / `sudo apt install ffmpeg` | | Models not downloaded | Inform user: first transcription will auto-download models (~60MB) to `~/.coli/models/` | If `coli` is missing, stop here and do not proceed. ### Step 0: Config Setup Follow `shared/config-pattern.md` Step 0. Initial defaults: ```bash # 当前目录: mkdir -p ".listenhub/asr" echo '{"model":"sensevoice","polish":true}' > ".listenhub/asr/config.json" CONFIG_PATH=".listenhub/asr/config.json" # 全局: mkdir -p "$HOME/.listenhub/asr" echo '{"model":"sensevoice","polish":true}' > "$HOME/.listenhub/asr/config.json" CONFIG_PATH="$HOME/.listenhub/asr/config.json" ``` Config summary display: ``` 当前配置 (asr)： 模型：sensevoice / whisper-tiny.en 润色：开启 / 关闭 ``` ### Setup Flow (first run or reconfigure) Ask in order: 1. **model**: "默认使用哪个语音识别模型？" - "sensevoice（推荐）" — 支持中英日韩粤，可检测语言、情绪、音频事件 - "whisper-tiny.en" — 仅英文 3. **polish**: "转录后由 AI 润色文本？（修正标点、去语气词、提升可读性）" - "是（推荐）" → `polish: true` - "否，保留原始转录" → `polish: false` Save all answers at once after collecting them. ### Step 1: Get Audio File If the user hasn't provided a file path, ask: > "请提供要转录的音频文件路径。" Verify the file exists before proceeding. ### Step 2: Confirm ``` 准备转录： 文件：{filename} 模型：{model} 润色：{是 / 否} 继续？ ``` ### Step 3: Transcribe Run `coli asr` with JSON output (to get metadata): ```bash coli asr -j --model {model} "{file}" ``` On first run, `coli` will automatically download the required model. This may take a moment — inform the user if models haven't been downloaded yet. Parse the JSON result to extract `text`, `lang`, `emotion`, `event`, `duration`. ### Step 4: Polish (if enabled) If `polish` is `true`, take the raw `text` from the transcription result and rewrite it to fix punctuation, remove filler words, and improve readability. Preserve the original meaning and speaker intent. Do not summarize or paraphrase. ### Step 5: Present Result Display the transcript directly in the conversation: ``` 转录完成 {transcript text} ───────────────── 语言：{lang} · 情绪：{emotion} · 时长：{duration}s ``` If polished, show the polished version with a note that it was AI-refined. Offer to show the raw original on request. ### Step 6: Export as Markdown (optional) After presenting the result, ask: ``` Question: "保存为 Markdown 文件到当前目录？" Options: - "是" — save to current directory - "否" — done ``` If yes, write `{audio-filename}-transcript.md` to the **current working directory** (where the user is running Claude Code). The file should contain the transcript text (polished version if polish was enabled), with a front-matter header: ```markdown --- source: {original audio filename} date: {YYYY-MM-DD} model: {model used} duration: {duration}s lang: {detected language} --- {transcript text} ``` ## Composability - **Invoked by**: future skills that need to transcribe recorded audio - **Invokes**: nothing ## Examples > "帮我转录这个文件 meeting.m4a" 1. Check prerequisites 2. Read config 3. Confirm: meeting.m4a, sensevoice, polish on 4. Run `coli asr -j --model sensevoice "meeting.m4a"` 5. Polish the raw text 6. Display inline > "transcribe interview.wav, no polish" 1. Check prerequisites 2. Read config 3. Override polish to false for this session 4. Run `coli asr -j --model sensevoice "interview.wav"` 5. Display raw transcript inline


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)