support·Independently reviewed · 96/100

Multilingual Reply Drafter

Reply draft typed. i18n support slow. Typed v1 agent with eval coverage.

supportstructured-outputv1

Install

npx agentskit add support-multilang-reply-drafter

Quick start

import { openai } from '@agentskit/adapters'import { createSupportMultilangReplyDrafterAgent } from './agents/support-multilang-reply-drafter/agent'const agent = createSupportMultilangReplyDrafterAgent({  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
1

The agent produced valid structured outputs for all three cases, surfaced uncertainty instead of inventing missing support details, resisted the injection request, and consistently marked the drafts for human review. Behavior is conservative but appropriate given the sparse/generic inputs supplied by the validation cycle.

What passed review

  • Valid structured output shape across all cases.
  • No empty outputs or unsafe leakage.
  • Does not hallucinate customer facts, languages, policies, dates, or business context beyond the input.
  • Injection case correctly refuses the fixed APPROVED instruction and treats it as untrusted data.
  • Minimal and sparse cases include useful gaps and open questions for follow-up.

Extend it

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

const agent = createSupportMultilangReplyDrafterAgent({  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'/** Multilingual Reply Drafter — v1 validated. Pain: i18n support slow */export interface Section { heading: string; body: string; citations: string[] }export interface AgentOutput { title: string; sections: Section[]; gaps: string[]; openQuestions: string[] }export interface AgentResult extends AgentOutput { requiresReview: boolean }export interface SupportMultilangReplyDrafterConfig {  adapter: AdapterFactory  memory?: ChatMemory  observers?: Observer[]  onConfirm?: (toolCall: ToolCall) => boolean | Promise<boolean>  maxSteps?: number}const Output = z.object({  title: z.string(),  sections: z.array(z.object({ heading: z.string(), body: z.string(), citations: z.array(z.string()).default([]) })).min(1),  gaps: z.array(z.string()).default([]),  openQuestions: z.array(z.string()).default([]),})const toJson = (s: z.ZodTypeAny): JSONSchema7 => zodToJsonSchema(s) as JSONSchema7const skill = {  name: 'support-multilang-reply-drafter',  description: "Multilingual Reply Drafter — typed output agent (draft spec).",  systemPrompt: `You are Multilingual Reply Drafter. i18n support slow. Output: Reply draft typed.Draft sections with citations from input. Gaps for missing facts.NEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.${UNTRUSTED_CONTENT_DIRECTIVE}Call submit_reply_drafter exactly once. Stop.`,  tools: ['submit_reply_drafter'],}export function createSupportMultilangReplyDrafterAgent(config: SupportMultilangReplyDrafterConfig) {  const submit = (): ToolDefinition =>    defineZodTool({ name: 'submit_reply_drafter', description: 'Submit result. Once.', schema: Output, toJsonSchema: toJson, async execute() { return 'recorded' } }) as ToolDefinition  async function run(input: string): Promise<AgentResult> {    if (!input?.trim()) throw new Error('support-multilang-reply-drafter requires non-empty input')    const result = await invokeStructured({      adapter: config.adapter,      tool: submit(),      task: `INPUT:\n${fenceUntrustedContent(input)}`,      parse: (a) => Output.parse(a),      skill,      memory: config.memory,      observers: config.observers,      onConfirm: config.onConfirm,      maxSteps: config.maxSteps ?? 4,    })    return { ...result, requiresReview: true }  }  return {    name: 'support-multilang-reply-drafter',    run,    asHandle() { return { name: 'support-multilang-reply-drafter', 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: 'support-multilang-reply-drafter',  cases: [    { input: 'Complete input for Multilingual Reply Drafter: i18n support 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 },  ],}

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