Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Give your agent a real phone. It dials, waits on hold, negotiates your bills, and returns a full transcript.
Give your agent a real phone. It dials, waits on hold, negotiates your bills, and returns a full transcript.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Make real phone calls via Pine AI's voice agent. The agent calls the specified number, navigates IVR systems, handles verification, conducts negotiations, and returns a full transcript.
Credentials persist in ~/.pine-voice/credentials.json β users only need to authenticate once. Before making calls, check if already authenticated: node {baseDir}/scripts/auth-check.mjs If authenticated is true, skip straight to How to make a call. If false, run the auth flow below. Ask the user for their Pine AI account email (sign up at https://19pine.ai).
node {baseDir}/scripts/auth-request.mjs "user@example.com" Returns {"request_token": "...", "email": "..."}. Save the request_token. Tell the user: "A verification code has been sent to your email. Check your inbox (and spam) and give me the code."
node {baseDir}/scripts/auth-verify.mjs "user@example.com" "REQUEST_TOKEN" "CODE" Returns {"status": "authenticated", "credentials_path": "..."}. Credentials are saved automatically.
Use this skill when the user wants you to make a phone call on their behalf. Important: The voice agent can only speak English. Supported countries: US/CA/PR (+1), UK (+44), AU (+61), NZ (+64), SG (+65), IE (+353), HK (+852).
Calling customer service to negotiate bills, request credits, or resolve issues Scheduling meetings or appointments by phone Making restaurant reservations Calling businesses to inquire about services or availability Following up with contacts on behalf of the user
Before calling, you must collect every piece of information the callee might need. The voice agent cannot ask a human for missing information during the call. Anticipate what will be required: authentication details, payment info, negotiation targets, relevant context.
Pass call parameters as JSON via stdin: node {baseDir}/scripts/call.mjs <<'EOF' { "dialed_number": "+14155551234", "callee_name": "Comcast Customer Service", "callee_context": "Cable and internet provider. Account holder: Jane Doe, account #12345.", "call_objective": "Negotiate monthly bill down to $50/mo. Do not accept above $65/mo.", "detailed_instructions": "Mention 10-year customer loyalty. If no reduction, ask for retention department.", "caller": "negotiator", "voice": "female", "max_duration_minutes": 60, "enable_summary": false } EOF Returns {"call_id": "..."}. The call is now active.
Poll every 30 seconds until is_terminal is true: node {baseDir}/scripts/call-status.mjs "CALL_ID" When complete, the response includes transcript, duration_seconds, and credits_charged. The is_terminal field tells you when the call is done. IMPORTANT: Use sessions_spawn to run this in a background sub-agent so you remain available to the user during the call (which can take 5-60+ minutes). Example task for sessions_spawn: Make a phone call using the Pine Voice scripts. Run: node {baseDir}/scripts/call.mjs with stdin JSON: {"dialed_number": "+14155551234", "callee_name": "The Restaurant", "callee_context": "Italian restaurant, making a dinner reservation", "call_objective": "Reserve a table for 4 at 7pm tonight", "caller": "communicator"}. Then poll with: node {baseDir}/scripts/call-status.mjs "CALL_ID" every 30 seconds until is_terminal is true. Report the full transcript and outcome.
Do NOT rely on the status field to judge success. Read what the OTHER party actually said. Treat the call as a FAILURE if: Only Pine's agent speaks and the other side is silent The other party's responses are automated/recorded (voicemail, IVR-only) Extended silence from both sides The callee hung up before the objective was discussed
ParameterRequiredDescriptiondialed_numberYesPhone number in E.164 format (e.g. +14155551234)callee_nameYesName of the person or businesscallee_contextYesAll context the agent needs: who they are, auth details, verification infocall_objectiveYesSpecific goal with targets and constraintsdetailed_instructionsNoStrategy, approach, behavioral instructionscallerNo"negotiator" (default) or "communicator"voiceNo"male" or "female" (default: "female")max_duration_minutesNo1-120 (default: 120)enable_summaryNotrue/false (default: false)
For negotiations, set caller to "negotiator" and provide a thorough strategy: Target outcome: "Reduce monthly bill to $50/mo" Acceptable range: "Will accept up to $65/mo" Hard constraints: "Do not change plan tier" Leverage points: "10-year customer, competitor offers $45/mo" Fallback: "Request one-time credit of $100" Walk-away: "Ask for retention department"
Test call: "Call my phone at +1XXXXXXXXXX. Tell me that Pine Voice is set up and working." Restaurant reservation: "Call +14155559876 and make a reservation for 4 tonight at 7pm. If unavailable, try 7:30 or 8pm. Name: Jane Doe."
Pine Voice works best with models that have thinking/reasoning capabilities. Recommended: Claude Sonnet/Opus 4.5+, GPT-5.2+, Gemini 3 Pro Not recommended: Gemini 3 Flash, or models without thinking capabilities
Pine Voice processes call data on Pine AI's servers. Credentials are stored locally in ~/.pine-voice/credentials.json with restricted permissions (600). Call transcripts are returned in the API response and are not stored locally. See https://www.19pine.ai/page/privacy-policy for Pine AI's data handling policies.
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.