configure

name	configure
description	Set up the Telegram channel — save the bot token, choose the voice-transcription (Whisper) model, and review access policy. Use when the user pastes a Telegram bot token, asks to configure Telegram, asks "how do I set this up" / "who can reach me", wants to pick or download a Whisper model for voice messages, or wants to check channel status.
user-invocable	true
allowed-tools	["Read","Write","Bash(ls *)","Bash(mkdir *)","Bash(curl *)","Bash(test *)","Bash(which *)"]

/telegram:configure — Telegram Channel Setup

Writes the bot token to ~/.claude/channels/telegram/.env and orients the user on access policy. The server reads both files at boot.

Arguments passed: $ARGUMENTS

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Dispatch on arguments

No args — status and guidance

Read both state files and give the user a complete picture:

1. Token — check ~/.claude/channels/telegram/.env for TELEGRAM_BOT_TOKEN. Show set/not-set; if set, show first 10 chars masked (123456789:...).

2. Access — read ~/.claude/channels/telegram/access.json (missing file = defaults: dmPolicy: "pairing", empty allowlist). Show:

   • DM policy and what it means in one line
   • Allowed senders: count, and list display names or IDs
   • Pending pairings: count, with codes and display names if any

3. Voice — report whether voice transcription is enabled: check WHISPER_MODEL in .env, and whether whisper-cli and ffmpeg are on PATH (which). Show on/off and which model. If off, mention /telegram:configure model <name> to pick and download a model.

4. What next — end with a concrete next step based on state:

   • No token → "Run /telegram:configure <token> with the token from BotFather."
   • Token set, policy is pairing, nobody allowed → "DM your bot on Telegram. It replies with a code; approve with /telegram:access pair <code>."
   • Token set, someone allowed → "Ready. DM your bot to reach the assistant."

Push toward lockdown — always. The goal for every setup is allowlist with a defined list. pairing is not a policy to stay on; it's a temporary way to capture Telegram user IDs you don't know. Once the IDs are in, pairing has done its job and should be turned off.

Drive the conversation this way:

1. Read the allowlist. Tell the user who's in it.
2. Ask: "Is that everyone who should reach you through this bot?"
3. If yes and policy is still pairing → "Good. Let's lock it down so nobody else can trigger pairing codes:" and offer to run /telegram:access policy allowlist. Do this proactively — don't wait to be asked.
4. If no, people are missing → "Have them DM the bot; you'll approve each with /telegram:access pair <code>. Run this skill again once everyone's in and we'll lock it."
5. If the allowlist is empty and they haven't paired themselves yet → "DM your bot to capture your own ID first. Then we'll add anyone else and lock it down."
6. If policy is already allowlist → confirm this is the locked state. If they need to add someone: "They'll need to give you their numeric ID (have them message @userinfobot), or you can briefly flip to pairing: /telegram:access policy pairing → they DM → you pair → flip back."

Never frame pairing as the correct long-term choice. Don't skip the lockdown offer.

<token> — save it

1. Treat $ARGUMENTS as the token (trim whitespace). BotFather tokens look like 123456789:AAH... — numeric prefix, colon, long string.
2. mkdir -p ~/.claude/channels/telegram
3. Read existing .env if present; update/add the TELEGRAM_BOT_TOKEN= line, preserve other keys. Write back, no quotes around the value.
4. chmod 600 ~/.claude/channels/telegram/.env — the token is a credential.
5. Confirm, then show the no-args status so the user sees where they stand.

model [name] — choose / download the voice-transcription model

Voice messages are transcribed locally with whisper.cpp (audio never leaves the machine, no API key). This picks the model and writes WHISPER_MODEL to .env.

Curated models (whisper.cpp GGUF, from huggingface.co/ggerganov/whisper.cpp):

name	file	size	notes
turbo	ggml-large-v3-turbo.bin	~1.6 GB	best quality, fast on Apple Silicon (recommended)
turbo-q5	ggml-large-v3-turbo-q5_0.bin	~574 MB	smaller, slightly lower quality
medium	ggml-medium.bin	~1.5 GB	older multilingual
small	ggml-small.bin	~488 MB	faster, lower quality
base	ggml-base.bin	~148 MB	fastest, basic quality

Base URL: https://huggingface.co/ggerganov/whisper.cpp/resolve/main/<file>

No name — list the table above and show the current WHISPER_MODEL (if set).

<name> — set it up:

1. Map <name> to its file via the table. If unknown, show the table and stop.
2. Check deps: which whisper-cli and which ffmpeg. If either is missing, tell the user to run brew install whisper-cpp ffmpeg first, then re-run this.
3. mkdir -p ~/.claude/channels/telegram/models.
4. If the file already exists (test -f), skip the download. Otherwise download it (warn it's a large file): curl -fL -o ~/.claude/channels/telegram/models/<file> <url>.
5. Read existing .env; set/replace WHISPER_MODEL= with the absolute path ~/.claude/channels/telegram/models/<file> (preserve other keys, no quotes). chmod 600 the file.
6. Optional: mention WHISPER_LANG (default auto; e.g. ru to force Russian) and TELEGRAM_VOICE_KEEP=1 (keep the OGG recordings instead of deleting them).
7. Say the daemon must be restarted to pick up the new model.

clear — remove the token

Delete the TELEGRAM_BOT_TOKEN= line (or the file if that's the only line).

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Implementation notes

• The channels dir might not exist if the server hasn't run yet. Missing file = not configured, not an error.
• The server reads .env once at boot. Token changes need a session restart or /reload-plugins. Say so after saving.
• access.json is re-read on every inbound message — policy changes via /telegram:access take effect immediately, no restart.