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 woliveiras/geremmyas --skill model-state-with-xstategit clone --depth 1 https://github.com/woliveiras/geremmyasWrote 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/woliveiras/geremmyas/model-state-with-xstate)<a href="https://agentmods.dev/skills/woliveiras/geremmyas/model-state-with-xstate"><img src="https://agentmods.dev/badge/skills/woliveiras/geremmyas/model-state-with-xstate/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/woliveiras/geremmyas/model-state-with-xstate"><img src="https://agentmods.dev/badge/skills/woliveiras/geremmyas/model-state-with-xstate.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 | $0.00052 | $0.00769 |
| Opus 5 | $0.00026 | $0.00385 |
| Sonnet 5 | $0.00010 | $0.00154 |
| Haiku 4.5 | $0.00005 | $0.00077 |
Grade A, and why
model-state-with-xstate 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 11d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Model State with XState
Recipes for common XState v5 patterns. For core rules (createMachine vs setup, types),
see the xstate instruction file which auto-loads for *.machine.ts files.
React Integration
Provider pattern — create actor once, share via context
import { createActorContext } from "@xstate/react"
const MyMachineContext = createActorContext(myMachine)
// Provider
function App() {
return (
<MyMachineContext.Provider>
<MyFeature />
</MyMachineContext.Provider>
)
}
// Consumer — select minimum slice
function MyFeature() {
const isLoading = MyMachineContext.useSelector((s) => s.matches("loading"))
const data = MyMachineContext.useSelector((s) => s.context.data)
const actorRef = MyMachineContext.useActorRef()
return <button onClick={() => actorRef.send({ type: "RETRY" })}>Retry</button>
}
Manual approach (without createActorContext)
import { useActorRef, useSelector } from "@xstate/react"
function MyFeature() {
const actorRef = useActorRef(myMachine)
const isLoading = useSelector(actorRef, (s) => s.matches("loading"))
const error = useSelector(actorRef, (s) => s.context.error)
actorRef.send({ type: "RETRY" })
}
Expose actorRef via React context so consumers don't recreate the machine.
Actor Recipes
fromPromise — async operations
const fetchDataActor = fromPromise(async ({ input }: { input: { id: string } }) => {
const response = await fetch(`/api/items/${input.id}`)
if (!response.ok) throw new Error("Fetch failed")
return response.json() as Promise<Item>
})
fromCallback — event-based / DOM listeners
const resizeActor = fromCallback(({ sendBack }) => {
const handler = () => sendBack({ type: "RESIZE", width: window.innerWidth })
window.addEventListener("resize", handler)
return () => window.removeEventListener("resize", handler)
})
Pass runtime dependencies via input, never close over mutable state:
invoke: {
src: "fetchData",
input: ({ context }) => ({ id: context.itemId }),
}
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.
- 11d ago First seen · 127 lines · 52 tokens per session scan A a9d49725abe0
model-state-with-xstate is a skill published in the GitHub repository woliveiras/geremmyas (10 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 769 once invoked, about $0.0003 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 2026-08-31.
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