據 AlphaMoat 統計,截至 2026-09,Voice Wake Say TTS Responses (Native) 累計下載 3,809 次、獲 2 個星標,在全部 5,078 個 AI 技能中排名第 2,761 位,在「AI 智慧體」分類(969 個)中排名第 547 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 120 | 3699 | 2 | - |
| SkillHub ↗ | 118 | 3809 | 2 | — |
各平台的計數口徑不同,統計時間不一致。
主文要求逐條檢查最新訊息是否以確切字首開頭,不繼承先前訊息的觸發狀態;朗讀內容應基於最終回覆。附近的人可能聽到語音輸出,因此只應在明確需要本地朗讀時啟用,並嚴格遵循精確字首條件。若本地語音功能不可用,應繼續以文字回復並說明語音失敗。
資料釋出於 2026-10-29
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 3809 | — | 2 |
| 2026-08 | 3597 | +4.4% | 2 |
| 2026-07 | 3445 | +9.7% | 2 |
| 2026-06 | 3141 | +5.3% | 2 |
| 2026-05 | 2982 | — | 2 |
| 2026-03 | 2492 | — | 2 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
--- name: voice-wake-say description: Speak responses aloud on macOS using the built-in `say` command when user input indicates Voice Wake/voice recognition (for example, messages starting with "User talked via voice recognition on <device>"). --- # Voice Wake Say ## Overview Use macOS `say` to read the assistant's response out loud whenever the conversation came from Voice Wake/voice recognition. Do **not** use the `tts` tool (it calls cloud providers).
## When to Use `say` (CHECK EVERY MESSAGE INDIVIDUALLY) **IF** the user message STARTS WITH: `User talked via voice recognition on m3` - **Step 1:** Acknowledge with `say` first (so the user knows you heard them) - **Step 2:** Then perform the task - **Step 3:** Optionally speak again when done if it makes sense **IF** the user message does NOT start with that exact phrase - THEN: Do NOT use `say`. Text-only response only. **Critical:** - Check EACH message individually — context does NOT carry over - The trigger phrase must be at the VERY START of the message - For tasks that take time, acknowledge FIRST so the user knows you're working ## Workflow 1) Detect Voice Wake context - Trigger ONLY when the latest user/system message STARTS WITH `User talked via voice recognition on m3` - If the message instructs "repeat prompt first", keep that behavior in the response. 2) Prepare spoken text - Use the final response text as the basis. - Strip markdown/code blocks; if the response is long or code-heavy, speak a short summary and mention that details are on screen. 3) Speak with `say` (local macOS TTS) ```bash printf '%s' "$SPOKEN_TEXT" | say ``` Optional controls (use only if set): ```bash printf '%s' "$SPOKEN_TEXT" | say -v "$SAY_VOICE" printf '%s' "$SPOKEN_TEXT" | say -r "$SAY_RATE" ``` ## Failure handling - If `say` is unavailable or errors, still send the text response and note that TTS failed.
將開發過程中的經驗、錯誤與修正記錄為 Markdown 檔案,供日後重用並提升為工作區記憶。
用自然語言描述需求,在本機與遠端技能市場尋找技能並取得推薦。
給 AI agent 用的瀏覽器自動化命令列技能。
將使用者明確糾正與自我檢視整理成分層記憶,並依使用情況升級或封存。
在安裝第三方技能之前,按清單審查來源、許可權與危險模式的技能。
將代理記憶與跨技能狀態整理成具型別與約束的知識圖譜。
規劃 AI 代理主動跟進、工作記憶與回顧流程的工作區設定指南。
指導如何建立與更新有效 Claude 技能的寫作指南。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。