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 daffy0208/ai-dev-standards --skill livestream-engineergit clone --depth 1 https://github.com/daffy0208/ai-dev-standardsWrote 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/daffy0208/ai-dev-standards/livestream-engineer)<a href="https://agentmods.dev/skills/daffy0208/ai-dev-standards/livestream-engineer"><img src="https://agentmods.dev/badge/skills/daffy0208/ai-dev-standards/livestream-engineer/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/daffy0208/ai-dev-standards/livestream-engineer"><img src="https://agentmods.dev/badge/skills/daffy0208/ai-dev-standards/livestream-engineer.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 | $0.00018 | $0.03261 |
| Opus 5 | $0.00009 | $0.01631 |
| Sonnet 5 | $0.00004 | $0.00652 |
| Haiku 4.5 | $0.00002 | $0.00326 |
Grade A, and why
livestream-engineer 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 10d 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 — 539 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Livestream Engineer Skill
I help you build live streaming features, implement WebRTC, and create real-time broadcasting experiences.
What I Do
Live Streaming:
- WebRTC peer-to-peer video
- Live broadcasting
- Screen sharing
- Real-time chat
Streaming Platforms:
- Twitch-style streaming
- Video conferencing
- Live events
- Webinars
WebRTC Basics
Peer-to-Peer Video Call
// lib/webrtc.ts
export class WebRTCConnection {
private peerConnection: RTCPeerConnection
private localStream: MediaStream | null = null
constructor() {
this.peerConnection = new RTCPeerConnection({
iceServers: [{ urls: 'stun:stun.l.google.com:19302' }]
})
}
async startLocalStream() {
try {
this.localStream = await navigator.mediaDevices.getUserMedia({
video: true,
audio: true
})
this.localStream.getTracks().forEach(track => {
this.peerConnection.addTrack(track, this.localStream!)
})
return this.localStream
} catch (error) {
console.error('Failed to get local stream:', error)
throw error
}
}
async createOffer() {
const offer = await this.peerConnection.createOffer()
await this.peerConnection.setLocalDescription(offer)
return offer
}
async handleAnswer(answer: RTCSessionDescriptionInit) {
await this.peerConnection.setRemoteDescription(answer)
}
async handleOffer(offer: RTCSessionDescriptionInit) {
await this.peerConnection.setRemoteDescription(offer)
const answer = await this.peerConnection.createAnswer()
await this.peerConnection.setLocalDescription(answer)
return answer
}
addIceCandidate(candidate: RTCIceCandidateInit) {
return this.peerConnection.addIceCandidate(candidate)
}
onTrack(callback: (stream: MediaStream) => void) {
this.peerConnection.ontrack = event => {
callback(event.streams[0])
}
}
onIceCandidate(callback: (candidate: RTCIceCandidate) => void) {
this.peerConnection.onicecandidate = event => {
if (event.candidate) {
callback(event.candidate)
}
}
}
close() {
this.localStream?.getTracks().forEach(track => track.stop())
this.peerConnection.close()
}
}
What ships with it
2 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.
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.
- 10d ago First seen · 539 lines · 18 tokens per session scan A 33ed294fe6fb
livestream-engineer is a skill published in the GitHub repository daffy0208/ai-dev-standards (36 stars, last pushed 8mo ago), licensed MIT. It adds 18 tokens to every session and 3,261 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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