How do I install the Autonoannounce skill?

Run npx skillmds@latest add dvcrn/autonoannounce in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Autonoannounce safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: executes scripts, makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Autonoannounce?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Autonoannounce free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Autonoannounce?

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Autonoannounce by dvcrn — Agent Skill

Name: Autonoannounce
Rating: 4.5 (4 reviews)
Author: dvcrn

Autonoannounce

Build, operate, and troubleshoot Autonoannounce local speaker text-to-speech using the queued pipeline (enqueue to worker to ElevenLabs to playback backend). Requires ELEVENLABS_API_KEY for network synthesis, with optional ELEVENLABS_VOICE_ID and ELEVENLABS_MODEL_ID for voice/model selection. Writes local runtime state to config/tts-queue.json, .openclaw/*, and audio/earcons/*. Uses https://api.elevenlabs.io for synthesis/preflight calls. Use when creating or improving low-latency fire-and-forget TTS flows, tuning burst behavior, validating queue performance, enforcing local-only speech policy, or debugging queue/worker playback failures.

dvcrn Updated Sep 8, 2026 32 repo stars

File contents

Local TTS Queue

Requirements

Required credential: ELEVENLABS_API_KEY
Recommended env vars: ELEVENLABS_VOICE_ID, ELEVENLABS_MODEL_ID
Runtime tools: python3, curl, and one local playback backend (mpv, ffplay, afplay, paplay, or PowerShell sound player)
Network destination for synthesis/preflight: https://api.elevenlabs.io

Overview

Use this skill to keep local speech fast, reliable, and policy-compliant by treating enqueue as fire-and-forget and isolating synthesis/playback inside the queue worker.

Quick start workflow

Confirm queue health with scripts/tts-queue-status.sh.
Enqueue speech with scripts/speak-local-queued.sh "text".
If audio does not play, inspect worker logs and runbook steps in references/runbook.md.
For latency tuning, run scripts/benchmark-autonoannounce.sh and compare against SLOs in references/perf-slos.md.

Operating rules

Keep the producer path non-blocking: enqueue then return immediately.
Keep synthesis/playback in worker-only execution paths.
Prefer fewer larger writes to the queue (coalesce bursty traffic when possible).
Use policy-safe output lanes: local speaker for protected users; no Discord voice-file fallback.
Treat one failed item as isolated: retry with bounds, then dead-letter; do not stall entire queue.

Commands

Enqueue: scripts/speak-local-queued.sh "<text>"
Worker (foreground): scripts/tts-queue-worker.sh
Worker daemon: scripts/tts-queue-daemon.sh
Status: scripts/tts-queue-status.sh
Benchmark harness: scripts/benchmark-autonoannounce.sh
- Fast foreground benchmark: scripts/benchmark-autonoannounce.sh 5
- Full diagnostic benchmark: scripts/benchmark-autonoannounce.sh 5 --status both --output full
First-run interactive setup: skills/autonoannounce/scripts/setup-first-run.sh (shell wrapper)
Cross-platform first-run CLI: skills/autonoannounce/scripts/setup_first_run.py
Backend detection (OS-aware): skills/autonoannounce/scripts/backend-detect.sh
ElevenLabs capability preflight: skills/autonoannounce/scripts/elevenlabs-preflight.sh (includes short 429 retry/backoff for SFX probe)
Earcon library manager (durable categories/cache): skills/autonoannounce/scripts/earcon-library.sh
Cross-platform playback runner: skills/autonoannounce/scripts/play-local-audio.sh
Playback backend/device probe: skills/autonoannounce/scripts/playback-probe.sh
Playback backend startup validator: skills/autonoannounce/scripts/playback-validate.sh
Playback confirmation tone: skills/autonoannounce/scripts/playback-test.sh
v0.2 smoke tests: skills/autonoannounce/scripts/test-v0.2.sh
Race/concurrency stress checks: skills/autonoannounce/scripts/race-stress.sh

References map

Runbook: references/runbook.md
Config contract: references/config-contract.md
Performance SLOs and interpretation: references/perf-slos.md
Foreground-latency optimization: references/front-path-optimization.md
Durable earcon categories and cache: references/earcon-library.md

Execution checklist

Verify prerequisites (ELEVENLABS_API_KEY, ELEVENLABS_VOICE_ID, mpv).
Validate queue paths and lock behavior before tuning performance.
Measure baseline before making queue/worker changes.
Re-run benchmark after each material change.
Record final p50/p95 latency and queue-wait deltas in the task summary.

---name: autonoannouncedescription: Build, operate, and troubleshoot Autonoannounce local speaker text-to-speech using the queued pipeline (enqueue to worker to ElevenLabs to playback backend). Requires ELEVENLABS_API_KEY for network synthesis, with optional ELEVENLABS_VOICE_ID and ELEVENLABS_MODEL_ID for voice/model selection. Writes local runtime state to config/tts-queue.json, .openclaw/*, and audio/earcons/*. Uses https://api.elevenlabs.io for synthesis/preflight calls. Use when creating or improving low-latency fire-and-forget TTS flows, tuning burst behavior, validating queue performance, enforcing local-only speech policy, or debugging queue/worker playback failures.---# Local TTS Queue## Requirements- Required credential: `ELEVENLABS_API_KEY`- Recommended env vars: `ELEVENLABS_VOICE_ID`, `ELEVENLABS_MODEL_ID`- Runtime tools: `python3`, `curl`, and one local playback backend (`mpv`, `ffplay`, `afplay`, `paplay`, or PowerShell sound player)- Network destination for synthesis/preflight: `https://api.elevenlabs.io`## OverviewUse this skill to keep local speech fast, reliable, and policy-compliant by treating enqueue as fire-and-forget and isolating synthesis/playback inside the queue worker.## Quick start workflow1. Confirm queue health with `scripts/tts-queue-status.sh`.2. Enqueue speech with `scripts/speak-local-queued.sh "text"`.3. If audio does not play, inspect worker logs and runbook steps in `references/runbook.md`.4. For latency tuning, run `scripts/benchmark-autonoannounce.sh` and compare against SLOs in `references/perf-slos.md`.## Operating rules- Keep the producer path non-blocking: enqueue then return immediately.- Keep synthesis/playback in worker-only execution paths.- Prefer fewer larger writes to the queue (coalesce bursty traffic when possible).- Use policy-safe output lanes: local speaker for protected users; no Discord voice-file fallback.- Treat one failed item as isolated: retry with bounds, then dead-letter; do not stall entire queue.## Commands- Enqueue: `scripts/speak-local-queued.sh "<text>"`- Worker (foreground): `scripts/tts-queue-worker.sh`- Worker daemon: `scripts/tts-queue-daemon.sh`- Status: `scripts/tts-queue-status.sh`- Benchmark harness: `scripts/benchmark-autonoannounce.sh` - Fast foreground benchmark: `scripts/benchmark-autonoannounce.sh 5` - Full diagnostic benchmark: `scripts/benchmark-autonoannounce.sh 5 --status both --output full`- First-run interactive setup: `skills/autonoannounce/scripts/setup-first-run.sh` (shell wrapper)- Cross-platform first-run CLI: `skills/autonoannounce/scripts/setup_first_run.py`- Backend detection (OS-aware): `skills/autonoannounce/scripts/backend-detect.sh`- ElevenLabs capability preflight: `skills/autonoannounce/scripts/elevenlabs-preflight.sh` (includes short 429 retry/backoff for SFX probe)- Earcon library manager (durable categories/cache): `skills/autonoannounce/scripts/earcon-library.sh`- Cross-platform playback runner: `skills/autonoannounce/scripts/play-local-audio.sh`- Playback backend/device probe: `skills/autonoannounce/scripts/playback-probe.sh`- Playback backend startup validator: `skills/autonoannounce/scripts/playback-validate.sh`- Playback confirmation tone: `skills/autonoannounce/scripts/playback-test.sh`- v0.2 smoke tests: `skills/autonoannounce/scripts/test-v0.2.sh`- Race/concurrency stress checks: `skills/autonoannounce/scripts/race-stress.sh`## References map- Runbook: `references/runbook.md`- Config contract: `references/config-contract.md`- Performance SLOs and interpretation: `references/perf-slos.md`- Foreground-latency optimization: `references/front-path-optimization.md`- Durable earcon categories and cache: `references/earcon-library.md`## Execution checklist- Verify prerequisites (`ELEVENLABS_API_KEY`, `ELEVENLABS_VOICE_ID`, `mpv`).- Validate queue paths and lock behavior before tuning performance.- Measure baseline before making queue/worker changes.- Re-run benchmark after each material change.- Record final p50/p95 latency and queue-wait deltas in the task summary.

Frequently asked questions