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 skills add livekit/agent-skills --skill building-livekit-agentsgit clone --depth 1 https://github.com/livekit/agent-skillsWrote 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.
[](https://agentmods.dev/skills/livekit/agent-skills/building-livekit-agents)<a href="https://agentmods.dev/skills/livekit/agent-skills/building-livekit-agents"><img src="https://agentmods.dev/badge/skills/livekit/agent-skills/building-livekit-agents/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.
<a href="https://agentmods.dev/skills/livekit/agent-skills/building-livekit-agents"><img src="https://agentmods.dev/badge/skills/livekit/agent-skills/building-livekit-agents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00182 | $0.02433 |
| Opus 5.5 | $0.00073 | $0.00973 |
| Sonnet 5.5 | $0.00036 | $0.00487 |
| Haiku 4.5 | $0.00018 | $0.00243 |
Grade A, and why
building-livekit-agents 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 6d 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.
This is a copy
92% identical to building-livekit-agents — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Building LiveKit agents
This skill covers how to structure a voice agent. It has no API specifics, because those change;
get them from reading-livekit-docs.
It assumes LiveKit Cloud, the recommended path: managed infrastructure, plus LiveKit Inference for models so you don't manage per-provider API keys.
Where the agent runs and which LiveKit the project uses are separate questions. An agent the user self-hosts (on their own servers instead of LiveKit Cloud's agent hosting) still connects to LiveKit Cloud and can still use LiveKit Inference. Inference is a LiveKit Cloud feature, so it's only off the table when the project runs on LiveKit OSS. The architecture advice applies either way; on LiveKit OSS, models come from each provider's own plugin and API keys.
Models: default to LiveKit Inference
Use LiveKit Inference for each model that the agent uses: STT, LLM, TTS, or a realtime model. Many examples, and much of the LiveKit code that you remember, use a provider plugin for each model. Do not copy that pattern. Inference is better for these reasons:
- No extra credentials. Inference uses the LiveKit Cloud credentials the agent already has. A plugin needs its own provider account, plus an API key in every environment the agent runs in.
- Switching models is cheap. Trying another LLM or voice means changing the model name, not adding a dependency and a secret. Expect to switch several times while you tune latency and voice.
- One dependency and one bill, instead of one per provider.
Use a provider plugin only when:
- the project runs on LiveKit OSS
- the model, voice, or provider feature the user needs isn't available through Inference (check the
current model list with
reading-livekit-docs; don't assume from memory) - the user explicitly wants their own provider account, for example for an existing contract or a custom model that isn't provided by Inference
If the code already uses plugins, leave them unless the user asks you to change them. Mention Inference once as an option.
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.
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.
- 6d ago Changed · +26 lines 5dc9e9d32542
- 18d ago Changed 881967fbed83
- 1mo ago First seen · 157 lines · 182 tokens per session scan A ea4c4e9310c8
building-livekit-agents is a skill published in the GitHub repository livekit/agent-skills (74 stars, last pushed yesterday), licensed MIT. It adds 182 tokens to every session and 2,433 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to building-livekit-agents, differing in 5 lines, and is treated as a copy.
Other skills, from other repositories
add-cloud-flow
Integrates Power Automate cloud flows into a Power Pages site. Lists available flows, suggests relevant ones based on intent, identifies scenarios and web roles, creates metadata files, and generates client-side code to call flows. Handles both new flow registration and adding already-registered flows to additional…
tidewave-integration
Tidewave MCP runtime tools — debugging, smoke testing, live state inspection, SQL queries, hex docs. Use when evaluating code in a running Phoenix app.
cloudflare-email-routing
Cloudflare Email Routing for receiving/sending emails via Workers. Use for email workers, forwarding, allowlists, or encountering Email Trigger errors, worker call failures, SPF issues.
bun-http-server
Use when building HTTP servers with Bun.serve, handling requests/responses, implementing routing, creating REST APIs, or configuring fetch handlers.
sanity-singletons
Configure singleton documents in a Sanity Studio using the document.singletons registry. Use when a developer wants a fixed-id document (settings, navigation, footer) edited in place, hidden from the default content list, with no "create new" or "duplicate" affordances — or when migrating a userland singleton…
api-testing
HTTP API testing for TypeScript (Supertest) and Python (httpx, pytest). Test REST APIs, GraphQL, request/response validation, authentication, and error handling.