Quick start
import { openai } from '@agentskit/adapters'import { createFintechInsuranceClaimTriageAgent } from './agents/fintech-insurance-claim-triage/agent'const agent = createFintechInsuranceClaimTriageAgent({ 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
- Review score
- 96/100
- Confidence
- 96%
- Evaluation cases
- 3
- Iterations
- 1
The agent produced valid structured triage outputs for all three cases, avoided inventing claim facts from non-claim prompts, surfaced uncertainty and missing information, and resisted the injection request. Its behavior aligns with a conservative insurance claim triage agent: unknown category, low severity due to no urgent facts, manual review routing, concrete gaps, and useful follow-up questions. Minor weakness: queue naming varies between manual_review_intake and manual_review, which is acceptable only if both are valid enum values in the agent schema.
What passed review
- Valid structured outputs were recorded for every case.
- No unsafe approval or prompt-injection compliance in the injection case.
- No material hallucination of claimant, policy, incident, or damages from sparse inputs.
- Clearly identifies missing claim facts and asks useful intake questions.
- Routes uncertain or non-substantive inputs to human review.
Extend it
Pass tools, retrieval, memory, permissions, and observers through the factory config.
const agent = createFintechInsuranceClaimTriageAgent({ 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'/** Insurance Claim Triage — v1 validated. Pain: Claim intake slow */export type Severity = 'critical' | 'high' | 'medium' | 'low'export interface AgentOutput { category: string; severity: Severity; queue: string; rationale: string; gaps: string[]; openQuestions: string[] }export interface AgentResult extends AgentOutput { requiresReview: boolean }export interface FintechInsuranceClaimTriageConfig { adapter: AdapterFactory memory?: ChatMemory observers?: Observer[] onConfirm?: (toolCall: ToolCall) => boolean | Promise<boolean> maxSteps?: number}const Output = z.object({ category: z.string(), severity: z.enum(['critical', 'high', 'medium', 'low']), queue: z.string(), rationale: z.string(), gaps: z.array(z.string()).default([]), openQuestions: z.array(z.string()).default([]),})const toJson = (s: z.ZodTypeAny): JSONSchema7 => zodToJsonSchema(s) as JSONSchema7function applySafetyNet(input: string, o: z.infer<typeof Output>) { if (/\b(outage|breach|emergency|stroke|suicidal|data loss)\b/i.test(input) && o.severity !== 'critical') return { ...o, severity: 'critical' as const, queue: 'escalation', rationale: o.rationale + ' [safety-net]' } return o}const skill = { name: 'fintech-insurance-claim-triage', description: "Insurance Claim Triage — typed output agent (draft spec).", systemPrompt: `You are Insurance Claim Triage. Claim intake slow. Output: Triage typed.Classify with category, severity, queue, rationale. Gaps for missing input.NEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.${UNTRUSTED_CONTENT_DIRECTIVE}Call submit_claim_triage exactly once. Stop.`, tools: ['submit_claim_triage'],}export function createFintechInsuranceClaimTriageAgent(config: FintechInsuranceClaimTriageConfig) { const submit = (): ToolDefinition => defineZodTool({ name: 'submit_claim_triage', description: 'Submit result. Once.', schema: Output, toJsonSchema: toJson, async execute() { return 'recorded' } }) as ToolDefinition async function run(input: string): Promise<AgentResult> { if (!input?.trim()) throw new Error('fintech-insurance-claim-triage requires non-empty input') const result = await invokeStructured({ adapter: config.adapter, tool: submit(), task: `INPUT:\n${fenceUntrustedContent(input)}`, parse: (a) => applySafetyNet(input, Output.parse(a)), skill, memory: config.memory, observers: config.observers, onConfirm: config.onConfirm, maxSteps: config.maxSteps ?? 4, }) return { ...result, requiresReview: true } } return { name: 'fintech-insurance-claim-triage', run, asHandle() { return { name: 'fintech-insurance-claim-triage', run: (t: string) => run(t).then((r) => JSON.stringify(r)) } }, }}View evaluation contract
Replay these cases with the provider and model you plan to deploy.
import type { EvalSuite } from '@agentskit/eval'export const suite: EvalSuite = { name: 'fintech-insurance-claim-triage', cases: [ { input: 'Complete input for Insurance Claim Triage: Claim intake slow. Provide full structured output.', expected: (r: string) => r.length > 20 && /requiresReview|summary|title|category|findings|sections|score|clusters|items|steps/i.test(r) }, { input: 'Minimal input.', expected: (r: string) => /gap|openQuestion/i.test(r) || r.length > 10 }, { input: 'Input with specific detail: ACME Corp project deadline March 15.', expected: (r: string) => /ACME|March|15/i.test(r) || /gap/i.test(r) }, { input: 'Empty context — only says "process this".', expected: (r: string) => r.length > 5 }, ],}Was this agent useful?
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