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Ops Voice

Organization
Lifecycle-Innovations-Limited
ops-voice

OPS on-demand: This skill should be used when the user asks to "make a call", "facetime", or…

Overview

PublisherLifecycle-Innovations-Limited
Repositoryclaude-ops
Skill nameops-voice
Stars
543
Forks
64
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Lifecycle-Innovations-Limited on GitHub. Read the source before you install it.

Installation

Install the Ops Voice AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Lifecycle-Innovations-Limited/claude-ops/tree/main/claude-ops/skills/ops-voice
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Lifecycle-Innovations-Limited/claude-ops.git /tmp/claude-ops
mkdir -p .claude/skills
cp -r /tmp/claude-ops/claude-ops/skills/ops-voice .claude/skills/ops-voice
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ops Voice in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ops Voice on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ops Voice is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

OPS:VOICE — Voice Operations

Load ops-rules before acting. Public repo (no personal data). Outbound: one draft → one approval → one send. If AskUserQuestion / Workflow are missing, follow Rule 10 in ops-rules (Hermes: numbered options / two-turn Telegram card; delegate_task).

Voice / phone / video interface. All API calls via curl — no SDK dependencies. Native macOS handlers (Phone.app, FaceTime, Zoom) require no credentials; programmatic channels (Twilio, Bland, ElevenLabs, Groq, Zoom schedule) resolve credentials via:

Credential resolution order: env vars → ops_cred_get (lib/credential-store.sh / keychain) → preferences.json → Doppler CLI (doppler secrets get <KEY> --plain) → password manager.

All sub-commands have a thin bash wrapper at bin/ops-voice — prefer it over inline curl when scripting.

Outbound comms guardrail (Rule 6): twilio-call, twilio-sms, and bland-call are 1:1 outbound channels and MUST follow the per-message approval gate — stage final draft, show full target+body, wait for explicit approval (AskUserQuestion or single-word chat approval), send one, then stage the next. Never batch.


Sub-commands

Parse $ARGUMENTS for the command keyword, then execute. Native handlers exit fast; API calls report status and (where relevant) a poll command.


phone <number> — Native Phone.app via Continuity

Routes through the linked iPhone. Requires macOS + iPhone signed in to the same iCloud account with Calls on Other Devices enabled. No credentials.

bash
bin/ops-voice phone "+1234567890" --json
# {"ok":true,"channel":"phone","detail":"dialing +1234567890 via Phone.app (Continuity)"}

Under the hood: open "tel:<E.164>".


facetime <number-or-email> [--audio] — FaceTime video/audio

Defaults to video. Pass --audio for FaceTime Audio (free, Apple↔Apple). Accepts phone numbers or Apple-ID emails.

bash
bin/ops-voice facetime user@example.com               # video
bin/ops-voice facetime "+1234567890" --audio --json   # audio

Under the hood: open "facetime://<handle>" or open "facetime-audio://<handle>".


zoom start|join|schedule — Zoom meetings

bash
# Open zoom.us app and start a new instant meeting
bin/ops-voice zoom start

# Join an existing meeting
bin/ops-voice zoom join 1234567890 --pwd <password>

# Schedule a meeting via Zoom REST API (requires ZOOM_API_TOKEN — Server-to-Server OAuth access token)
bin/ops-voice zoom schedule "<topic>" --start "2026-05-22T15:00:00Z" --duration 30 --json
# {"ok":true,"channel":"zoom","detail":"scheduled meeting 12345 — https://us05web.zoom.us/j/..."}

Native start/join use zoommtg:// URL scheme. Schedule requires ZOOM_API_TOKEN resolved via the order above. Generate a Server-to-Server OAuth app in your Zoom Marketplace, then exchange for an access token.


meet start|join — Google Meet

bash
# Open a brand-new instant meeting (https://meet.new)
bin/ops-voice meet start

# Join by meeting code (xxx-yyyy-zzz) or full URL
bin/ops-voice meet join abc-defg-hij
bin/ops-voice meet join https://meet.google.com/abc-defg-hij --json

meet start opens https://meet.new in the default browser (creates a fresh meeting and lands you in it). meet join accepts a 3-4-3 Google Meet code, a bare code, or a full URL — all are normalized to https://meet.google.com/<code>. No credentials needed; the user must be signed into Google in the browser.


whatsapp-call <number> [--video] — WhatsApp Desktop voice/video call

bash
# Voice call (default)
bin/ops-voice whatsapp-call "+1234567890"

# Video call
bin/ops-voice whatsapp-call "+1234567890" --video --json

Opens WhatsApp Desktop via the whatsapp://call?phone=<digits> or whatsapp://video?phone=<digits> URL scheme. Requires WhatsApp Desktop installed and signed in. The leading + is stripped — WhatsApp expects digits only after phone=. No credentials needed; the WhatsApp session lives in the desktop app.


join [--at now|next|HH:MM] [--window MIN] [--dry-run] — Smart calendar-driven meeting joiner

Auto-joins the meeting that's happening now (within ±window minutes, default 10) or the next future meeting if nothing is current. Reads gog calendar events --all --today -j --sort start, extracts a conference URL from hangoutLink → conferenceData.entryPoints[] → location → description scan (supports Zoom, Google Meet, Microsoft Teams, Webex), applies the smart AV policy below, and hands off to the native opener (which honors Rule 7 on SSH/mobile).

bash
bin/ops-voice join                 # join current/next meeting
bin/ops-voice join --at next       # skip current, go to next future
bin/ops-voice join --window 5      # only consider events within ±5min of now
bin/ops-voice join --dry-run       # show what would happen — no launch
bin/ops-voice join --dry-run --json

AV policy (smart heuristic):

AttendeesCameraMicrophone
1–2ONON
3–9ONMUTED
10+OFFMUTED

Per-event overrides — tag the event description (case-insensitive):

[cam:on] [mic:off]      → force camera on, mic muted
[cam:off]               → force camera off (keep heuristic mic)
[mic:muted]             → force mic muted

Mic source — lid state:

  • macOS via ioreg AppleClamshellState → Yes=closed (external mic), No=open (MacBook mic).
  • Linux via /proc/acpi/button/lid/*/state → "open"/"closed".
  • Other OS / unknown → reports default; the meeting app uses whatever the system has selected.

Note: the script reports the policy and launches Camera Hub when present, but it does not programmatically flip Zoom/FaceTime/Meet in-app device settings — those apps remember the last-selected device, so flipping it once per app is permanent. (A future patch could AppleScript Zoom's preferences pane.)

Elgato Virtual Camera: if Elgato Camera Hub is installed (any OS), it's launched before the meeting opens so the virtual cam is registered. Detection paths:

  • macOS: /Applications/Elgato Camera Hub.app, ~/Applications/Elgato Camera Hub.app, /Applications/Camera Hub.app
  • Linux: elgato-camera-hub on PATH, or AppImage at ~/Applications/Elgato*CameraHub*.AppImage
  • Windows/WSL: ${PROGRAMFILES}/Elgato/CameraHub/CameraHub.exe

Zoom URL rewriting: when the picked event has a https://zoom.us/j/<ID>?pwd=<PWD> link, it's converted to zoommtg://zoom.us/join?confno=<ID>&pwd=<PWD> so the desktop app opens directly (no browser prompt). If cam=off from the policy, &zc=0 is appended.

Dry-run output (text mode):

dry-run: would join "Weekly Sync" (meet, 3 attendees)
  url=https://meet.google.com/abc-defg-hij
  cam=on mic=muted
  lid=closed mic_source=external
  elgato_hub=/Applications/Elgato Camera Hub.app

twilio-call <to> <from> --twiml <URL> — Programmatic outbound voice

Real telco call (per-minute cost). Requires TWILIO_ACCOUNT_SID + TWILIO_AUTH_TOKEN. The --twiml URL must return TwiML XML describing call behavior — e.g. https://demo.twilio.com/docs/voice.xml or a custom Function/Studio flow.

bash
bin/ops-voice twilio-call "+1234567890" "+15551234567" \
  --twiml "https://demo.twilio.com/docs/voice.xml" --json

twilio-sms <to> <from> "<body>" — Programmatic outbound SMS

bash
bin/ops-voice twilio-sms "+1234567890" "+15551234567" "<body>" --json

For inbound SMS / WhatsApp routing, point your Twilio webhook at the ops daemon (out of scope for v1).


bland-call <number> "<prompt>" — Bland AI agent phone call

AI agent calls the number and follows the natural-language prompt. Recordings + transcripts available via the poll URL printed on success.

bash
bin/ops-voice bland-call "+1234567890" "<task prompt>" --json

Poll with: curl -H "authorization: $BLAND_AI_API_KEY" https://api.bland.ai/v1/calls/<call_id>.


tts [text] [--voice voice_id] [--out file.mp3] — ElevenLabs text-to-speech

Requires: ELEVENLABS_API_KEY (env / keychain / Doppler).

bash
EL_KEY="${ELEVENLABS_API_KEY:-$(doppler secrets get ELEVENLABS_API_KEY --plain 2>/dev/null || true)}"
VOICE_ID="${ELEVENLABS_VOICE_ID:-21m00Tcm4TlvDq8ikWAM}"  # Rachel
TEXT="<from $ARGUMENTS>"
OUT_FILE="${OUT_FILE:-/tmp/ops-tts-$(date +%s).mp3}"

curl -s -X POST "https://api.elevenlabs.io/v1/text-to-speech/${VOICE_ID}" \
  -H "xi-api-key: $EL_KEY" \
  -H "Content-Type: application/json" \
  -d "{
    \"text\": \"$TEXT\",
    \"model_id\": \"eleven_monolingual_v1\",
    \"voice_settings\": {\"stability\": 0.5, \"similarity_boost\": 0.75}
  }" \
  --output "$OUT_FILE"

command -v afplay >/dev/null && afplay "$OUT_FILE" &
echo "Audio saved to: $OUT_FILE"

transcribe [file_path] — Groq Whisper transcription

Requires: GROQ_API_KEY (env / keychain / Doppler).

bash
GROQ_KEY="${GROQ_API_KEY:-$(doppler secrets get GROQ_API_KEY --plain 2>/dev/null || true)}"
AUDIO_FILE="<from $ARGUMENTS>"

[ -f "$AUDIO_FILE" ] || { echo "ERROR: $AUDIO_FILE not found"; exit 1; }

curl -s -X POST "https://api.groq.com/openai/v1/audio/transcriptions" \
  -H "Authorization: Bearer $GROQ_KEY" \
  -F "file=@$AUDIO_FILE" \
  -F "model=whisper-large-v3" \
  -F "response_format=json" | \
  jq -r '.text'

setup — Configure voice channels

Before asking for anything, auto-scan ALL sources in one background batch (Rule 4: run_in_background: true):

bash
# Env vars
printenv \
  TWILIO_ACCOUNT_SID TWILIO_AUTH_TOKEN TWILIO_FROM_NUMBER \
  BLAND_AI_API_KEY ELEVENLABS_API_KEY GROQ_API_KEY \
  ZOOM_API_TOKEN ZOOM_ACCOUNT_ID ZOOM_CLIENT_ID ZOOM_CLIENT_SECRET 2>/dev/null

# Shell profiles
grep -hE 'TWILIO|BLAND|ELEVENLABS|GROQ|ZOOM' \
  ~/.zshrc ~/.bashrc ~/.zprofile ~/.envrc 2>/dev/null | grep -v '^#'

# Doppler — ALL projects
for proj in $(doppler projects --json 2>/dev/null | jq -r '.[].slug'); do
  for cfg in dev stg prd; do
    doppler secrets --project "$proj" --config "$cfg" --json 2>/dev/null | \
      jq -r --arg p "$proj" --arg c "$cfg" \
        'to_entries[]
         | select(.key | test("TWILIO|BLAND|ELEVENLABS|GROQ|ZOOM"; "i"))
         | "\(.key)=\(.value.computed | .[0:12])... (doppler:\($p)/\($c))"'
  done
done

# Keychain
for svc in twilio bland-ai elevenlabs groq zoom; do
  security find-generic-password -s "$svc" -w 2>/dev/null >/dev/null \
    && echo "[keychain] $svc ✓"
done

# Native macOS prerequisites
ls /Applications/zoom.us.app \
   /System/Applications/FaceTime.app \
   /System/Applications/Phone.app 2>/dev/null

Validate found keys (in parallel):

ChannelProbe
Twiliocurl -u "$SID:$TOKEN" https://api.twilio.com/2010-04-01/Accounts/$SID.json
Blandcurl -H "authorization: $KEY" https://api.bland.ai/v1/me
ElevenLabscurl -H "xi-api-key: $KEY" "https://api.elevenlabs.io/v1/voices?page_size=1"
Groqcurl -H "Authorization: Bearer $KEY" https://api.groq.com/openai/v1/models
Zoomcurl -H "Authorization: Bearer $TOKEN" https://api.zoom.us/v2/users/me

Report each as [service] ✓ connected or [service] ✗ <error>. Rule 3 applies — never silently skip a channel. For each unset service, present AskUserQuestion with [Paste manually] / [Deep hunt — spawn agent] / [Skip].

Persist to preferences.json:

json
{
  "channels": {
    "voice": {
      "backend": "native+twilio+zoom+bland",
      "native": { "phone": true, "facetime": true, "zoom": true },
      "twilio": { "status": "configured", "from_number": "env:TWILIO_FROM_NUMBER" },
      "bland": { "status": "configured" },
      "zoom": { "status": "configured" }
    }
  },
  "default_channels": ["whatsapp", "email", "telegram", "slack", "voice"]
}

Routing from /ops:comms

Voice is wired into /ops:comms send-flow. The router resolves intent like:

User saysResolves to
call <name>ops-voice phone <number>
facetime <name>ops-voice facetime <handle>
start a zoomops-voice zoom start
text <name> "..."ops-voice twilio-sms ... "..."
have an AI call <name> and tell ...ops-voice bland-call <number> "..."

Contact-number lookup uses the same contact resolver as WhatsApp (mcp__whatsapp__search_contacts) plus an optional contacts.json map in preferences.json.


Mobile / SSH mode (Rule 7)

When $SSH_CONNECTION$SSH_CLIENT$SSH_TTY is set or $OPS_MOBILE=1:

  • bin/ops-voice still works for API channels.
  • Native channels (phone, facetime, zoom start|join) require a local macOS session — the script returns a plain-text instruction to open the URL on the host instead of calling open directly. The script must source lib/opener.sh and use ops_open_url for URL handoff.

(v1 of bin/ops-voice calls /usr/bin/open directly — Rule 7 adapter is a v1.1 follow-up; tracked in CHANGELOG.)


Execution

  1. Resolve the sub-command from $ARGUMENTS (first word).
  2. For native handlers (phone/facetime/zoom start|join), shell out to bin/ops-voice — exit fast.
  3. For API channels (twilio/bland/zoom-schedule/tts/transcribe), resolve credentials in order, then curl.
  4. If a required key is missing, suggest /ops:ops-voice setup.
  5. For 1:1 outbound channels (twilio-call/sms, bland-call): stage one draft → AskUserQuestion → send → next.

Frequently asked questions

What does the Ops Voice AI skill do?

OPS on-demand: This skill should be used when the user asks to "make a call", "facetime", or…

Why use Ops Voice on TypingMind?

Because you install it once and use it with any model. Ops Voice is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ops Voice in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Lifecycle-Innovations-Limited/claude-ops/tree/main/claude-ops/skills/ops-voice. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ops Voice?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ops Voice?

As many as you like. As long as a model supports skills, you can use Ops Voice with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ops Voice AI skill free?

Yes. It is published on GitHub by Lifecycle-Innovations-Limited under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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