81-pipecat

81-pipecat is a skill for Claude Code, Codex from majiayu000/claude-skill-registry. It costs 18 tokens per session (2,911 once invoked), scanned A, original, MIT.

A learning skill for Pipecat, a framework for building voice AI agents—software that can listen, process speech, and respond—with services such as speech recognition and language models.

In plain words
What is it for?
Use it while learning to build voice bots, create reusable Pipecat guidance, connect AI services, and improve a Pipecat skill.
Why use it?
It teaches Pipecat through its frame-based design, where audio, text, responses, and control signals move through processing steps. It also explains how Pipecat differs from LiveKit Agents.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths.

Good fit Use it while learning to build voice bots, create reusable Pipecat guidance, connect AI services, and improve a Pipecat skill.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/majiayu000/claude-skill-registry/81-pipecat
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add majiayu000/claude-skill-registry --skill 81-pipecat
Clone the repo
git clone --depth 1 https://github.com/majiayu000/claude-skill-registry

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for 81-pipecat

README.md
[![agentmods](https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/81-pipecat/github.svg)](https://agentmods.dev/skills/majiayu000/claude-skill-registry/81-pipecat)
Your own site
<a href="https://agentmods.dev/skills/majiayu000/claude-skill-registry/81-pipecat"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/81-pipecat/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for 81-pipecat

Your own site · 80×15
<a href="https://agentmods.dev/skills/majiayu000/claude-skill-registry/81-pipecat"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/81-pipecat.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,911 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Agent Snooping · line 36
    Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.
    Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.02911
Opus 5 $0.00009 $0.01456
Sonnet 5 $0.00004 $0.00582
Haiku 4.5 $0.00002 $0.00291

Measured 12d ago against content hash dffb469b6f8d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

81-pipecat scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/agent/81-pipecat/SKILL.md · 350 lines

How it starts

The opening of the file, as written. The whole thing — 350 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Build Your Pipecat Skill

Before learning Pipecat—a frame-based voice AI framework with 40+ provider integrations—you'll own a Pipecat skill.

This is skill-first learning. You build the skill, then the chapter teaches you what it knows and how to make it better. By the end, you have a production-ready voice agent AND a reusable skill for building more.


Why Pipecat?

Pipecat started as an internal framework at Daily.co for building voice bots. After the team saw how well it worked, they open-sourced it in 2024. Since then, it has grown to over 8,900 GitHub stars and supports 40+ AI service integrations.

The framework's key insight: everything is a frame. Audio data, text transcriptions, LLM responses, control signals—all frames flowing through a pipeline of processors. This simple abstraction enables powerful composition: swap providers with one line, add custom processing anywhere, deploy to any transport.

What you're learning: A compositional approach to voice AI that gives you maximum flexibility.


Pipecat vs LiveKit

You learned LiveKit Agents in Chapter 80. Here's how Pipecat differs:

Dimension LiveKit Agents Pipecat
Core Abstraction Jobs (distributed work) Frames (data flow)
Architecture Workers, Sessions, Agents Pipelines, Processors, Transports
Provider Strategy Curated integrations Plugin ecosystem (40+)
Transport WebRTC-first Transport-agnostic
Turn Detection Semantic (transformer) Configurable (VAD-based)

Neither is "better"—they solve different problems. LiveKit excels at enterprise scale and semantic understanding. Pipecat excels at flexibility and rapid iteration.


Step 1: Clone Skills-Lab Fresh

Every chapter starts fresh. No state assumptions.

  1. Go to github.com/panaversity/claude-code-skills-lab
  2. Click the green Code button
  3. Select Download ZIP
  4. Extract the ZIP file
  5. Open the extracted folder in your terminal

Read the full file on GitHub · 350 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 350 lines · 18 tokens per session scan A dffb469b6f8d

Subscribe to this mod's changes

81-pipecat is a skill published in the GitHub repository majiayu000/claude-skill-registry (600 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 2,911 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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