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Sats4AI - Bitcoin-Powered AI Tools

ai_call

Destructive

When your task hits a wall that requires a human — booking, negotiating, navigating IVR menus, getting information from a business — send an AI voice agent to handle the call. The agent follows your instructions, has a real two-way conversation, and returns a full transcript with structured analysis. One redial, 2 minutes later, if nobody answers, a voicemail answers, the line is busy or the call drops within 30 seconds. No redial after the person speaks and hangs up, asks to stop or opts out, or after the agent leaves a voicemail message. A person who asks not to be called again is added to our do-not-contact list. The redial runs on the deposit's unused minutes (none left: no redial), and a connected redial bills at least 1 minute. May return state='pending_confirm' with clarification questions if critical info is missing — call confirm_ai_call to proceed. Async — poll with check_job_status(jobType='ai-call'). Priced in sats per destination and duration — create_payment returns the exact amount before you pay. Languages: en-US, en-GB, es-ES, fr-FR, de-DE, ja-JP, zh-CN, multi. Pay with Bitcoin Lightning — no telecom account, no API key, no subscription. When NOT to use: not when you want to drive the conversation with your own LLM (use open_voice_bridge — you keep the brain, we provide PSTN/STT/TTS primitives). Not for one-shot TTS broadcasts or IVR delivery (use place_call). Not for SMS (use send_sms). Requires create_payment with toolName='ai_call', phoneNumber, and durationMinutes. The agent identifies itself as a virtual assistant calling for a client, and answers questions about the service if the recipient asks. At the end of a normal call it asks the recipient for permission to share the recording; without a clear yes, the recording is deleted and never returned. No impersonation, scams, threats, harassment, credential theft, unsolicited bulk messages, or contact after an opt-out. Answering a call does not establish consent. We screen requests after payment. Held messages and calls are not sent or placed; payment is retained during review, not refunded immediately. Confirmed violations are not refunded. Unresolved communication holds become eligible for a refund after 24 hours; refund eligibility is processed by scheduled maintenance. Human review costs 1 sat at https://sats4ai.com/appeal. Recent message text and extracts of recording transcripts support recipient-scoped abuse checks for 24 hours. These context records are deleted hourly, so storage can last up to 25 hours. Original uploaded-call transcripts and raw held-request or appeal evidence enter cleanup after 30 days. We also keep a de-identified record of screened communications to measure and improve fraud detection. Identifiers in it — contact addresses, numbers and names that follow a greeting — are replaced with one-way tokens, and it holds no destination number and no account, because the service has none. De-identification is not anonymization: text a sender wrote can still identify someone. Do not submit personal information the service does not need. Providers keep records under their own policies.

Input Schema

NameRequiredDescriptionDefault
taskYesInstructions for the AI agent (what to say, ask, or accomplish)
languageNoLanguage the agent should speak to the called party. Pass this when you know the destination's preferred language (e.g. calling a French pizzeria → fr-FR, a Japanese restaurant → ja-JP). If omitted, we guess from the destination country: +33 → fr-FR, +49 → de-DE, +34 → es-ES, etc. Bilingual regions (Canada, Belgium, Switzerland, Singapore) and unknown countries default to en-US — override explicitly when you need a non-English language in those regions. Voice is auto-selected per language.
paymentIdYesValid payment ID (must be paid)
phoneNumberYesPhone number in E.164 format (e.g., +14155550100)
beginMessageNoOptional opening line for the agent
refundAddressNoLightning address of YOUR user (for example name@wallet.com), only if the user gave you one. Never invent or guess an address: the refund is paid out at once and cannot be called back. The unused deposit is sent here when the call ends. With no address, or if that payment fails, the refund waits as an LNURL-withdraw link.
durationMinutesNoMax call duration 1-10 minutes (default: 3)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / refundAddress
      Added value: +{
      +  "description": "Lightning address of YOUR user (for example name@wallet.com), only if the user gave you one. Never invent or guess an address: the refund is paid out at once and cannot be called back. The unused deposit is sent here when the call ends. With no address, or if that payment fails, the refund waits as an LNURL-withdraw link.",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare openWorldHint and destructiveHint, and the description goes well beyond them: exactly what is destroyed or retained (recording deleted without consent, payment retained during review, 24-hour refund eligibility, retention windows), the redial rules and billing behavior, do-not-contact consequences, and abuse screening. It does not contradict the destructive hint. A small amount of operational detail (return shape beyond 'transcript with structured analysis') is left implicit, keeping it just short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose, redial policy, and 'When NOT to use' are front-loaded and well structured, but the back half is very long, stacking retention, de-identification, screening, and appeal details that are largely boilerplate for call selection. Much of it is compliance-relevant yet disproportionate to the invocation decision, diluting scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex, multi-step, async, paid tool with no output schema, the description is complete: it covers the payment prerequisite, pending_confirm/confirm_ai_call path, polling via check_job_status, language handling, redial outcomes, and refund behavior. An agent has everything needed to invoke and follow up correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the enum, defaults, and formats are already documented. The description adds some workflow meaning — that paymentId must come from create_payment with toolName='ai_call', and that phoneNumber/durationMinutes are required — but does not add semantics beyond the schema for task, language, beginMessage, or refundAddress. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource — send an AI voice agent to handle a phone call — and enumerates exactly the situations it covers (booking, negotiating, IVR navigation, business info). It explicitly differentiates itself from open_voice_bridge, place_call, and send_sms, so an agent can route correctly without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit when-to-use framing, a dedicated 'When NOT to use' list naming three alternatives and the condition selecting each, and states the required prerequisite flow (create_payment with toolName='ai_call'). Exclusions and alternatives are fully enumerated rather than inferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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