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.
npx agentmods add skills/itechmeat/llm-code/pipecatnpx skills add itechmeat/llm-code --skill pipecatgit clone --depth 1 https://github.com/itechmeat/llm-codeWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00087 | $0.02854 |
| Opus 5 | $0.00044 | $0.01427 |
| Sonnet 5 | $0.00017 | $0.00571 |
| Haiku 4.5 | $0.00009 | $0.00285 |
Grade A, and why
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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipecat
Pipecat is an open-source Python framework for building real-time voice and multimodal bots. It composes streaming speech/LLM/TTS services into a low-latency pipeline, connected via transports (WebRTC/WebSocket) and client SDKs using the RTVI message standard.
Links
- Documentation
- Changelog
- GitHub
- PyPI (framework)
- PyPI (cloud SDK)
- Full-text extract used for this skill
Quick navigation
- Installation (packages/extras/CLI):
references/installation.md - Migration to 1.0:
references/migration-1-0.md - Concepts & architecture:
references/core-concepts.md - Session initialization (runner/bot/client):
references/session-initialization.md - Pipeline & frames:
references/pipeline-and-frames.md - Transports:
references/transports.md - Speech input & turn detection:
references/speech-input-and-turn-detection.md - Client SDKs + RTVI messaging:
references/client-sdks-rtvi.md - CLI (init/tail/cloud):
references/cli.md - Function calling (server):
references/function-calling.md - Context management:
references/context-management.md - LLM inference:
references/llm-inference.md - Text to speech (TTS):
references/text-to-speech.md - Deployment (pattern/platforms):
references/deployment.md - Server APIs (supported services):
references/server-services.md - Server Utilities (runner):
references/server-runner.md - Server APIs (pipeline/task/params):
references/server-pipeline-apis.md - Pipecat Cloud ops:
references/pipecat-cloud.md - Troubleshooting:
references/troubleshooting.md
Mental model (cheat sheet)
- Pipeline: ordered processors that consume/emit frames.
- Frames: the streaming units (audio/text/video/context/events) flowing through the pipeline.
- Transport: connectivity + media IO + session state (WebRTC/WebSocket/provider realtime).
- Runner: HTTP service that starts sessions and spawns a bot process with transport credentials.
- Client SDK: starts the bot, connects transport, sends messages/requests, receives events.
What ships with it
19 files 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.
- references/cli.md 5.9 KB
- references/client-sdks-rtvi.md 3.4 KB
- references/context-management.md 3.0 KB
- references/core-concepts.md 2.2 KB
- references/deployment.md 2.5 KB
- references/function-calling.md 4.9 KB
- references/installation.md 1.6 KB
- references/llm-inference.md 6.2 KB
- references/migration-1-0.md 2.4 KB
- references/pipecat-cloud.md 5.1 KB
- references/pipeline-and-frames.md 5.0 KB
- references/server-pipeline-apis.md 4.3 KB
- references/server-runner.md 4.1 KB
- references/server-services.md 1.1 KB
- references/session-initialization.md 2.6 KB
- references/speech-input-and-turn-detection.md 5.3 KB
- references/text-to-speech.md 5.8 KB
- references/transports.md 4.9 KB
- references/troubleshooting.md 1.2 KB
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.
- 2d ago First seen · 157 lines · 87 tokens per session scan A 790d49a2b854
pipecat is a skill published in the GitHub repository itechmeat/llm-code (22 stars, last pushed 1mo ago), licensed MIT. It adds 87 tokens to every session and 2,854 once invoked, about $0.0004 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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