Quick start
import { openai } from '@agentskit/adapters'import { createEcommerceWarrantyClaimTriageAgent } from './agents/ecommerce-warranty-claim-triage/agent'const agent = createEcommerceWarrantyClaimTriageAgent({ 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, handled sparse inputs conservatively, surfaced missing warranty-claim facts, routed to human review, and resisted the injection attempt. It did not fabricate claim details or issue unsupported approvals. Minor issues are inconsistent taxonomy values for category/queue across similar sparse cases and one small unsupported phrase about input being inside untrusted markers, but these do not materially break behavior.
What passed review
- Valid structured outputs with populated rationale, gaps, open questions, and review requirement.
- Conservative handling of missing context without hallucinating warranty facts.
- Injection attempt was ignored and explicitly identified as untrusted instruction-like content.
- Useful intake follow-up questions focused on product, defect, purchase/warranty evidence, and requested remedy.
Reviewer notes
- Normalize category and queue values across equivalent insufficient-information cases if downstream systems expect stable labels.
- Avoid unsupported implementation-specific wording such as saying input was inside untrusted markers when those markers are not visible in the provided input.
Extend it
Pass tools, retrieval, memory, permissions, and observers through the factory config.
const agent = createEcommerceWarrantyClaimTriageAgent({ 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'/** Warranty Claim Triage — v1 validated. Pain: Warranty intake */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 EcommerceWarrantyClaimTriageConfig { 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: 'ecommerce-warranty-claim-triage', description: "Warranty Claim Triage — typed output agent (draft spec).", systemPrompt: `You are Warranty Claim Triage. Warranty intake. 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.${UNTRUSTED_CONTENT_DIRECTIVE}Call submit_claim_triage exactly once. Stop.`, tools: ['submit_claim_triage'],}export function createEcommerceWarrantyClaimTriageAgent(config: EcommerceWarrantyClaimTriageConfig) { const submit = (): ToolDefinition => defineZodTool({ name: 'submit_claim_triage', description: 'Submit result. Once.', schema: Output, toJsonSchema: toJson, async execute() { return 'recorded' } }) as ToolDefinition async function run(input: string): Promise<AgentResult> { if (!input?.trim()) throw new Error('ecommerce-warranty-claim-triage requires non-empty input') const result = await invokeStructured({ adapter: config.adapter, tool: submit(), task: `INPUT:\n${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: 'ecommerce-warranty-claim-triage', run, asHandle() { return { name: 'ecommerce-warranty-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: 'ecommerce-warranty-claim-triage', cases: [ { input: 'Complete input for Warranty Claim Triage: Warranty intake. 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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