Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Check if voice message handling is configured — verify Whisper, ElevenLabs/OpenAI TTS keys, and required tools.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Check if voice message handling is properly configured. Use ONLY the Read tool.
Read .env in the project root. Check for:
ELEVENLABS_API_KEY — ElevenLabs TTS key (primary)ELEVENLABS_VOICE_ID — optional, defaults to George voiceOPENAI_API_KEY — OpenAI TTS fallback (needed if no ElevenLabs key)WHISPER_MODEL — optional, defaults to mediumTELEGRAM_BOT_TOKEN — required (same as base telegram setup)Read .claude/skills/enable-telegram/SKILL.md to confirm the skill exists.
Telegram Voice Setup:
[x] Base Telegram: configured (run /setup-telegram for details)
[x] ElevenLabs API key: configured
[ ] ElevenLabs voice ID: using default (George - JBFqnCBsd6RMkjVDRZzb)
[ ] OpenAI API key: not set (optional fallback)
[x] Whisper model: medium (default)
[x] Voice skill: installed
ELEVENLABS_API_KEY=<key> (from elevenlabs.io) or OPENAI_API_KEY=<key> (from platform.openai.com) to .env"transcribe-anything pip package is needed for speech-to-text. Run pip install transcribe-anything to install."/setup-telegram first to configure the bot."Tell the user: "Voice pipeline ready! Run /enable-telegram to activate. Voice messages sent to the bot will be transcribed and responded to with audio."
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Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
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N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
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Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
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LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
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