Uses an AI-driven structured check to read recent headlines and classify them; arms branch on the structured outputs.

Provided free and as is, without warranty of any kind — including merchantability, fitness for a particular purpose, and the accuracy or completeness of any result. See the licence. You are responsible for checking what this produces before relying on it.

News Sentiment Check

Uses the check.ai: structured AI check to read recent news and classify the overall tenor. The when: arms then branch on the structured outputs the AI returned.

What it does

On each fire, the monitor's check is NOT a tool call — it's a direct AI call. The check:

Sends a prompt describing what to look for.
Declares an outputs: map naming the structured fields the AI must return (with each field's description as a hint).
Gets a JSON object back with those keys filled in.
Each key becomes a binding the when: arms can reference directly.

The arms then evaluate the structured outputs:

Arm 1 — urgency >= 4: high-urgency catch-all. Notifies regardless of tenor.
Arm 2 — tenor == bearish: caught only if urgency was 1-3 (arm 1 didn't match first). Notifies on bearish tenor.
Else — quiet day or neutral/bullish tenor below the urgency threshold.

Edit before installing

In monitor.iml:

check.ai.prompt — rewrite for your domain ("today's crypto news", "ops channel chat from the last hour", "internal status reports"). Be specific about what you want classified and what dimensions matter.
check.ai.outputs — declare the structured fields you want. The description text matters — it's literally the hint the AI gets for what to put in each field. Be precise.
The when: arms reference outputs by name (e.g. tenor == bearish, urgency >= 4). Match these to whatever you declared in outputs:.

Bindings used

These come from check.ai.outputs, not from a tool. The names are whatever you declare:

{{summary}} — paragraph string the AI wrote
{{tenor}} — one-token classification: bullish | bearish | mixed | quiet
{{urgency}} — integer 1-5

Add or rename fields by editing check.ai.outputs: — the bindings update automatically (they're named after the keys you declared).

Requirements

AI assistant configured (Server Settings → AI Assistant — provider, API key, model). If no AI is configured, the check fails soft and the arms never fire.

Pattern showcase

check.ai is the structured-output AI check. Unlike an ai: arm (which returns true/false), check.ai returns a map of named fields that the arms then evaluate against. Use it when:

The thing you're watching is fuzzy and can't be a tool call ("is the news bearish today?", "does the support inbox have an escalation?").
You want a SINGLE AI call per fire, then cheap arm evaluation.
You want structured downstream routing (different arms for different outputs).

Tokens: 1 LLM call per fire. Schedule accordingly.