Getting an AI to place a phone call takes an evening. The trouble starts after that. It said "your table is booked" when the restaurant had said no such thing. It talked to a voicemail greeting for two minutes, politely asking for a reservation. It accepted a price above the budget because the conversation had a nice flow. All three happened on real calls to my own phone. So I built a runtime that takes the completion decision away from the model and gives it to code. https://github.com/FORIFOR/oathra What it does npx oathra demo Two AIs start a phone call in your browser, no API key. One plays a restaurant, the other wants a table. 7 pm is full, the restaurant offers 7:30, the caller takes it, gives a name, and only when the restaurant says "you're all set" does the run become MISSION COMPLETE. The result is not a summary. Every field is anchored to something the other party said. { "field": "time", "value": "19:30", "source": "callee", "transcript": "7 is fully booked, but we do have 7:30.", "span": "7:30", "explicit": true, "verified": true } Completion is a formula, not an opinion: complete = connected ∧ date.verified ∧ time.verified ∧ partySize.verified ∧ confirmed.verified ∧ constraints hold If the caller says "great, that's confirmed", it is recorded and ignored. Only the callee's "you're booked" fills confirmed. The evidence rules This part is deterministic parsers and rules. No LLM. "7 is full, but 7:30 works" → no evidence for 7:00 (negated clause) "the 13th, sorry, the 14th" → the 14th survives, with a supersede trail "probably fine" → neither agreement nor confirmation price changes after "you're booked" → the confirmation goes stale and must be re-obtained "OK, I'll look elsewhere" → not an acceptance There is a command that generates ten thousand hostile clerks to break this: oathra eval --adversarial 10000 # never-confirm / wrong-restate / negate-then-offer / silent-hangup / caller-echo-trap # False Completion: 0 / 10000 adversarial runs The fuzzer caught real bugs. The first one: "¥21,100" was split at the comma, became "¥100", and the agent happily accepted. More recently I let GPT-4o mini and Gemini play the clerk (oathra eval --callee openai), which found refusals that quoted a number being read as offers, and product names being parsed as serial numbers. Real phone calls The same runtime drives real calls. oathra setup phone # pick a voice engine and a carrier oathra phone doctor # which layer is broken oathra call --to +81… # dial Carriers (Twilio direct, or Plivo / your own SIP through a LiveKit gateway) and voice engines (GPT-Live, OpenAI Realtime, Deepgram + LLM + TTS) are chosen independently. Calls to my own phone: # Stack What happened 1 Deepgram + GPT-4o-mini + TTS 11.8 s to first reply. It kept asking "can you hear me?" 2 Same, streaming TTS 2.2 s. Talked to voicemail for 2 minutes; noise interrupted it 13 times 3 GPT-Live (full duplex) ~0.4 s. A 6 min 25 s chat with no errors Call three was when it felt usable. GPT-Live is $0.05/min for the session; Twilio to a Japanese mobile is ¥28.78/min. Where it honestly stands Twilio direct and GPT-Live are verified on real calls Plivo and custom SIP are implemented from provider docs; PSTN not yet verified MCP server is v0.2 Every number above was measured by me and can be reproduced with the commands in the README. Scenarios are YAML and welcome as PRs. https://forifor.github.io/oathra/en/