Agent skill · software engineering · sickn33
pipecat-friday-agent
Build a low-latency, Iron Man-inspired tactical voice assistant (F.R.I.D.A.Y.) using Pipecat, Gemini, and OpenAI.
Why this skill is useful
Adds a complete executable pipeline for building a tactical voice assistant with integration scripts for multiple AI providers.
What it needs
Requires pipecat-ai, python-dotenv installed locally. Requires google, openai account access. About 2k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
Pipecat Friday Agent Overview This skill provides a blueprint for building F.R.I.D.A.Y. (Replacement Integrated Digital Assistant Youth), a local voice assistant inspired by the tactical AI from the Iron Man films. It uses the Pipecat framework to orchestrate a low-latency pipeline: STT: OpenAI Whisper (whisper-1) or gpt-4o-transcribe LLM: Google Gemini 2.5 Flash (via a compatibility shim) TTS: OpenAI TTS (nova voice) Transport: Local Audio (Hardware Mic/Speakers) When to Use This Skill Use when you want to build a real-time, conversational voice agent. Use when working with the Pipecat framework for pipeline-based AI. Use when you need to integrate multiple providers (Google and OpenAI) into a single voice loop. Use when building Iron Man-themed or tactical-themed voice applications. How It Works Step 1: Install Dependencies You will need the Pipecat framework and its service providers installed: Step 2: Configure Environment Create a .env file with your API keys: Step 3: Run the Agent Execute the provided Python script to start the interface: Core Concepts Pipeline Architecture The agent follows a linear pipeline: Mic -> VAD -> STT -> LLM -> TTS -> Speaker. This allows for granular control over each stage, unlike end-to-end speech-to-speech models. Google Compatibility Shim Since Google's Gemini API has a different message format than OpenAI's standard (which Pipecat aggregators expect), the script includes a GoogleSafeContext and GoogleSafeMessage class to bridge the gap. Best Practices ✅ Use Silero VAD: It is robust for local hardware and prevents background noise from triggering the LLM. ✅ Concise Prompts: Tactical agents should give short, data-dense responses to minimize latency. ✅ Sample Rate Match: OpenAI TTS outputs at 24kHz; ensure your audiooutsamplerate matches to avoid high-pitched or slowed audio. ❌ No Polite Fillers: Avoid "Hello, how can I help you today?" Instead, use "Systems nominal. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/pipecat-friday-agent--5fcbed