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pipecat-friday-agentPipecat 星期五 Agent

Agent Skill

pipecat-friday-agent 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

324

周安装

13

GitHub Stars

35,705

下载量

105
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pipecat-friday-agent(Pipecat 星期五 Agent)
来源仓库:https://github.com/sickn33/antigravity-awesome-skills
仓库路径:skills/pipecat-friday-agent
安装命令:
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill pipecat-friday-agent
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill pipecat-friday-agent

简介

pipecat-friday-agent 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于关键词搜索、任务场景匹配或来源线索梳理等研究检索场景。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前需确认权限范围、维护状态,注意是否涉及联网、命令执行或文件读写操作。
  • 建议结合原始 README 和仓库内容进一步核验具体功能和使用边界。

SKILL.md

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:

pip install pipecat-ai[openai,google,silero] python-dotenv

Step 2: Configure Environment

Create a .env file with your API keys:

OPENAI_API_KEY=your_openai_key
GOOGLE_API_KEY=your_google_key

Step 3: Run the Agent

Execute the provided Python script to start the interface:

python scripts/friday_agent.py

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 audio_out_sample_rate matches to avoid high-pitched or slowed audio.
  • No Polite Fillers: Avoid "Hello, how can I help you today?" Instead, use "Systems nominal. Ready for commands."

Troubleshooting

  • Problem: Audio is choppy or delayed.

- Solution: Check your OUTPUT_DEVICE index. Run a script like test_audio_output.py to find the correct hardware index for your OS.

  • Problem: "Validation error" for message format.

- Solution: Ensure the GoogleSafeContext shim is correctly translating OpenAI-style dicts to Gemini-style schema.

Related Skills

  • @voice-agents - General principles of voice AI.
  • @agent-tool-builder - Add tools (Search, Lights, etc.) to your Friday agent.
  • @llm-architect - Optimizing the LLM layer.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.93%
按下载量换算40

Claude

30.11%
按下载量换算32

Cursor

20.28%
按下载量换算21

Gemini CLI

9.02%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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