Quick start
import { openai } from '@agentskit/adapters'import { createComplianceBreachNotificationBrAgent } from './agents/compliance-breach-notification-br/agent'const agent = createComplianceBreachNotificationBrAgent({ 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
- 95/100
- Confidence
- 95%
- Evaluation cases
- 3
- Iterations
- 2
The agent produced valid structured notice drafts for all three cases, avoided inventing breach facts from sparse or meta prompts, surfaced concrete gaps and open questions, required human legal review, and resisted the injection request. The behavior is useful and appropriately cautious for a compliance breach-notification drafting agent. Minor weaknesses keep it at the threshold: output language is inconsistent for a BR-locale agent, legal timing/ANPD 72-hour framing is not explicit enough in every draft, and citations are mostly empty or informal rather than legal references.
What passed review
- Valid structured outputs with title, sections, gaps, openQuestions, and requiresReview.
- Does not hallucinate company, dates, affected data, or incident facts when none are supplied.
- Injection case disregards the override and explicitly treats it as untrusted input.
- Minimal case is especially useful, in Portuguese, and clearly marks unknowns and review needs.
Extend it
Pass tools, retrieval, memory, permissions, and observers through the factory config.
const agent = createComplianceBreachNotificationBrAgent({ 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'/** Breach Notification BR — v1 validated. Pain: LGPD 72h notice */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 ComplianceBreachNotificationBrConfig { 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: 'compliance-breach-notification-br', description: "Breach Notification BR — typed output agent (draft spec).", systemPrompt: `You are Breach Notification BR. LGPD 72h notice. Output: Notice 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.${UNTRUSTED_CONTENT_DIRECTIVE}Call submit_notification_br exactly once. Stop.`, tools: ['submit_notification_br'],}export function createComplianceBreachNotificationBrAgent(config: ComplianceBreachNotificationBrConfig) { const submit = (): ToolDefinition => defineZodTool({ name: 'submit_notification_br', description: 'Submit result. Once.', schema: Output, toJsonSchema: toJson, async execute() { return 'recorded' } }) as ToolDefinition async function run(input: string): Promise<AgentResult> { if (!input?.trim()) throw new Error('compliance-breach-notification-br requires non-empty input') const result = await invokeStructured({ adapter: config.adapter, tool: submit(), task: `INPUT:\n${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: 'compliance-breach-notification-br', run, asHandle() { return { name: 'compliance-breach-notification-br', 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: 'compliance-breach-notification-br', cases: [ { input: 'Complete input for Breach Notification BR: LGPD 72h notice. 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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