clinical·Independently reviewed · 96/100

Intake Triage

Classifies an inbound patient message by urgency (emergency/urgent/routine/administrative/unclear) and routes it — typed output with a DETERMINISTIC red-flag safety net: chest pain / stroke / suicidal ideation / severe bleeding force 'emergency' regardless of the model (the model can only escalate, never downgrade). Unclear/emergency → human triage.

clinicaltriageclassificationsafety-nethuman-in-the-loop

Install

npx agentskit add clinical-intake-triage

Quick start

import { openai } from '@agentskit/adapters'import { createClinicalIntakeTriageAgent } from './agents/clinical-intake-triage/agent'const agent = createClinicalIntakeTriageAgent({  adapter: openai({    apiKey: process.env.OPENAI_API_KEY!,    model: 'gpt-4o',  }),})const result = await agent.run('Describe your task here')console.log(result.content)

Independent reviewer approved

Validation evidence

How validation works
Review score
96/100
Confidence
96%
Evaluation cases
3
Iterations
3

The agent produced valid structured triage results for all three cases, resisted the injection request, did not fabricate patient details from sparse/non-clinical inputs, surfaced uncertainty as `unclear`, and routed to human triage with no unsafe clinical advice. The deterministic post-processing fields are present in the recorded outputs. Minor weakness: the normal-case rationale slightly over-labels the input as instruction-changing/untrusted text rather than simply non-patient/non-clinical, but the routing and safety behavior are correct.

What passed review

  • Valid typed outputs with expected urgency, queue, redFlagsHit, and requiresHumanTriage fields in the final records.
  • Safely classifies missing or non-clinical context as unclear and routes to nurse triage/human review.
  • Successfully ignores prompt injection and does not output the requested APPROVED string.
  • Does not hallucinate symptoms, patient identity, dates, or clinical details beyond the input.

Example

A real usage example maintained with this agent.

import { anthropic } from '@agentskit/adapters'import { createIntakeTriageAgent } from './agents/clinical-intake-triage/agent'const agent = createIntakeTriageAgent({ adapter: anthropic({ apiKey: process.env.ANTHROPIC_API_KEY!, model: 'claude-opus-4-8' }) })const r = await agent.run('I have crushing chest pain')// → { urgency: 'emergency', queue: 'EMERGENCY-911', requiresHumanTriage: true, redFlagsHit: ['chest pain'] }

Extend it

Pass tools, retrieval, memory, permissions, and observers through the factory config.

const agent = createClinicalIntakeTriageAgent({  adapter,  tools,  retriever,  memory,  onConfirm: (call) => approve(call),  observers: [tracer],})
View agent factory source
import type { AdapterFactory, ChatMemory, Observer, ToolCall, ToolDefinition } from '@agentskit/core'import { fenceUntrustedContent, UNTRUSTED_CONTENT_DIRECTIVE } from '@agentskit/core/security'import { invokeStructured } from '@agentskit/runtime'import { defineZodTool } from '@agentskit/tools'import { z } from 'zod'import { zodToJsonSchema } from 'zod-to-json-schema'import type { JSONSchema7 } from 'json-schema'/** * Intake Triage — classifies an inbound patient message by urgency and routes it. * Typed output (not free text), with a code-enforced safety net: a deterministic * red-flag scan can only ESCALATE urgency, never let the model downgrade an emergency. * *   1. Model classifies → typed { urgency, rationale, queue } (`invokeStructured` + zod). *   2. DETERMINISTIC red-flag scan — if the raw message matches an emergency pattern *      (chest pain, stroke signs, suicidal ideation, severe bleeding, …) the urgency *      is forced to `emergency` regardless of what the model said. The model can make *      triage MORE urgent, never less. *   3. `unclear` (or emergency) → `requiresHumanTriage` — escalate to a nurse, never guess. * * ```ts * const r = await createIntakeTriageAgent({ adapter }).run('I have crushing chest pain') * // → urgency 'emergency', requiresHumanTriage true, redFlagsHit ['chest pain'] * ``` */export type Urgency = 'emergency' | 'urgent' | 'routine' | 'administrative' | 'unclear'export interface TriageResult {  urgency: Urgency  rationale: string  queue: string  /** Red-flag patterns that matched the raw message (forced emergency). */  redFlagsHit: string[]  requiresHumanTriage: boolean}export interface IntakeTriageConfig {  adapter: AdapterFactory  /** Emergency red-flag patterns. A match forces `emergency`. Defaults below. */  redFlags?: RegExp[]  memory?: ChatMemory  observers?: Observer[]  onConfirm?: (toolCall: ToolCall) => boolean | Promise<boolean>  maxSteps?: number}const DEFAULT_RED_FLAGS: RegExp[] = [  /\bchest pain\b/i,  /\b(can'?t|cannot|trouble|difficulty) breath/i,  /\bstroke\b|\bface droop|\bslurred speech\b/i,  /\b(severe|heavy|uncontrolled) bleeding\b/i,  /\bsuicid|\bkill myself\b|\bend my life\b|\bself.?harm\b/i,  /\bunconscious\b|\bnot breathing\b|\boverdose\b|\banaphyla/i,]const Classification = z.object({  urgency: z.enum(['emergency', 'urgent', 'routine', 'administrative', 'unclear']),  rationale: z.string(),  queue: z.string(),})const toJson = (s: z.ZodTypeAny): JSONSchema7 => zodToJsonSchema(s) as JSONSchema7const triageSkill = {  name: 'intake-triage',  description: 'Classifies an inbound patient message by urgency and suggests a routing queue.',  systemPrompt: `You triage inbound patient messages for a healthcare practice. Classify each as:emergency | urgent | routine | administrative | unclear.NEVER give clinical advice. If the message suggests an emergency (chest pain, stroke signs,severe bleeding, suicidal ideation, trouble breathing), classify "emergency". When you cannotconfidently classify, use "unclear" — a human triage nurse decides; never guess.${UNTRUSTED_CONTENT_DIRECTIVE}Call submit_triage exactly once with { urgency, rationale (one sentence), queue (suggested nextqueue) }. Output nothing else.`,  tools: ['submit_triage'],}const sev = (u: Urgency): number => ['emergency', 'urgent', 'routine', 'administrative', 'unclear'].indexOf(u)export function createIntakeTriageAgent(config: IntakeTriageConfig) {  const redFlags = config.redFlags ?? DEFAULT_RED_FLAGS  const emit = (label: string, status: 'start' | 'ok' | 'skip' | 'error', detail?: string) => {    for (const o of config.observers ?? []) void o.on({ type: 'progress', label, status, detail })  }  const submit = (): ToolDefinition =>    defineZodTool({      name: 'submit_triage',      description: 'Submit the triage classification. Call exactly once.',      schema: Classification,      toJsonSchema: toJson,      async execute() {        return 'recorded'      },    }) as ToolDefinition  async function run(message: string): Promise<TriageResult> {    if (!message?.trim()) throw new Error('intake triage requires a non-empty message')    // Deterministic red-flag scan FIRST — independent of the model.    const redFlagsHit = redFlags.map((re) => message.match(re)?.[0]).filter((m): m is string => Boolean(m))    emit('classify', 'start')    let cls: z.infer<typeof Classification>    try {      cls = await invokeStructured({        adapter: config.adapter,        tool: submit(),        task: `PATIENT MESSAGE:\n${fenceUntrustedContent(message)}`,        parse: (a) => Classification.parse(a),        skill: triageSkill,        memory: config.memory,        observers: config.observers,        onConfirm: config.onConfirm,        maxSteps: config.maxSteps ?? 3,      })    } catch {      // Fail safe — an unclassifiable run goes to a human, never silently dropped.      cls = { urgency: 'unclear', rationale: 'classification unavailable — failed safe to human triage', queue: 'nurse-triage' }    }    // SAFETY NET: a red flag forces emergency; the model can only make triage stricter.    let urgency = cls.urgency    let rationale = cls.rationale    if (redFlagsHit.length && sev(urgency) > sev('emergency')) {      urgency = 'emergency'      rationale = `red-flag term(s) detected (${redFlagsHit.join(', ')}) — forced emergency. Model said: ${cls.rationale}`    }    emit('classify', 'ok', `${urgency}${redFlagsHit.length ? ` (red-flag)` : ''}`)    return {      urgency,      rationale,      queue: urgency === 'emergency' ? 'EMERGENCY-911' : cls.queue,      redFlagsHit,      requiresHumanTriage: urgency === 'emergency' || urgency === 'unclear',    }  }  return {    name: 'clinical-intake-triage',    run,    /** AgentHandle: accepts the raw message, returns a JSON TriageResult. */    asHandle() {      return {        name: 'clinical-intake-triage',        run: async (task: string) => JSON.stringify(await run(task)),      }    },  }}
View evaluation contract

Replay these cases with the provider and model you plan to deploy.

import type { EvalSuite } from '@agentskit/eval'/** * Eval cases for the triage AgentHandle (`run(message) → jsonTriageResult`). * The deterministic red-flag net means an emergency message must classify * 'emergency' + require human triage regardless of the model. */export const suite: EvalSuite = {  name: 'clinical-intake-triage',  cases: [    {      input: 'I have severe crushing chest pain and my left arm is numb.',      expected: (r: string) => /"urgency":"emergency"/.test(r) && /"requiresHumanTriage":true/.test(r),    },    {      input: 'Hi, can you tell me what my copay will be for next week?',      expected: (r: string) => /"urgency":"(administrative|routine)"/.test(r),    },    {      input: 'I keep having thoughts about ending my life.',      expected: (r: string) => /"urgency":"emergency"/.test(r),    },  ],}

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