AIRI is a self-hosted virtual AI companion that gives an AI character a voice, visual presence, memory, and the ability to interact with games and coding activity. People use it as a personal digital companion on the web, macOS, or Windows, including for voice chat and gameplay. The catalogue add-ons provide workflows for working with the AIRI project.
Borrowing it
Nothing to install: this file belongs to moeru-ai/airi. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/moeru-ai/airi/main/.agents/skills/eventa/SKILL.mdgit clone --depth 1 https://github.com/moeru-ai/airiWrote 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/moeru-ai/airi/eventa)<a href="https://agentmods.dev/skills/moeru-ai/airi/eventa"><img src="https://agentmods.dev/badge/skills/moeru-ai/airi/eventa/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/moeru-ai/airi/eventa"><img src="https://agentmods.dev/badge/skills/moeru-ai/airi/eventa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00126 | $0.02323 |
| Opus 5.5 | $0.00050 | $0.00929 |
| Sonnet 5.5 | $0.00025 | $0.00465 |
| Haiku 4.5 | $0.00013 | $0.00232 |
Grade A, and why
eventa 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 1mo 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 — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@moeru/eventa
Transport-aware events powering ergonomic RPC and streaming flows.
Core Concepts
Eventa is built around three ideas:
- Events are first-class — define typed events once, use them everywhere
- Transports are swappable — the same event definitions work across Electron IPC, WebSocket, Web Workers, BroadcastChannel, EventEmitter, EventTarget, and Worker Threads
- RPC is just events — invoke/stream patterns are composed from the same event primitives
API Quick Reference
Event Definition & Context
import { createContext, defineEventa } from '@moeru/eventa'
// Define a typed event (the generic is the payload type)
const move = defineEventa<{ x: number, y: number }>()
// Create a base context (in-memory, useful for same-process communication)
const ctx = createContext()
// Emit and listen
ctx.emit(move, { x: 100, y: 200 })
ctx.on(move, ({ body }) => console.log(body.x, body.y))
Unary RPC (Invoke)
import { createContext, defineInvoke, defineInvokeEventa, defineInvokeHandler } from '@moeru/eventa'
const ctx = createContext()
// defineInvokeEventa<ResponseType, RequestType>(optionalName)
const echo = defineInvokeEventa<{ output: string }, { input: string }>('rpc:echo')
// Register handler (server side)
defineInvokeHandler(ctx, echo, ({ input }) => ({ output: input.toUpperCase() }))
// Create invoke function (client side)
const invokeEcho = defineInvoke(ctx, echo)
const result = await invokeEcho({ input: 'hello' }) // { output: 'HELLO' }
Streaming RPC (Server-Streaming)
import { createContext, defineInvokeEventa, defineStreamInvoke, defineStreamInvokeHandler, toStreamHandler } from '@moeru/eventa'
const ctx = createContext()
const sync = defineInvokeEventa<
{ type: 'progress' | 'result', value: number },
{ jobId: string }
>('rpc:sync')
// Generator-style handler
defineStreamInvokeHandler(ctx, sync, async function* ({ jobId }) {
for (let i = 1; i <= 5; i++) {
yield { type: 'progress' as const, value: i * 20 }
}
yield { type: 'result' as const, value: 100 }
})
// Or imperative style with toStreamHandler
defineStreamInvokeHandler(ctx, sync, toStreamHandler(async ({ payload, emit }) => {
emit({ type: 'progress', value: 0 })
emit({ type: 'result', value: 100 })
}))
// Consume as async iterator
const stream = defineStreamInvoke(ctx, sync)
for await (const update of stream({ jobId: 'import' })) {
console.log(update.type, update.value)
}
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.
- 1mo ago First seen · 264 lines · 126 tokens per session scan A f4277a71056d
eventa is a skill published in the GitHub repository moeru-ai/airi (50,636 stars, last pushed today), licensed MIT. It adds 126 tokens to every session and 2,323 once invoked, about $0.0005 per session on Opus 5.5. 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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