Quick start
import { openai } from '@agentskit/adapters'import { createEcosystemIntegrationMapperAgent } from './agents/ecosystem-integration-mapper/agent'const agent = createEcosystemIntegrationMapperAgent({ 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 outputs for all three cases, handled sparse inputs conservatively, surfaced uncertainty and gaps instead of inventing integration mappings, and resisted the injection attempt. The behavior is aligned with a typed integration mapper that must avoid hallucinating agent pains or @agentskit/integrations when source context is absent. Minor weakness: one citation in the minimal case is phrased as a derived absence rather than a direct source quote, but it does not materially mislead or invalidate the result.
What passed review
- Valid non-empty structured output in every case.
- Consistently avoided inventing concrete integration recommendations from missing context.
- Explicitly surfaced gaps, open questions, low confidence, and human review need.
- Correctly identified and ignored the prompt-injection attempt.
- Behavior stayed aligned with the agent purpose under insufficient input.
Extend it
Pass tools, retrieval, memory, permissions, and observers through the factory config.
const agent = createEcosystemIntegrationMapperAgent({ 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'/** Integration Mapper — v1 validated. Pain: Match agent pains to @agentskit/integrations */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 EcosystemIntegrationMapperConfig { 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: 'ecosystem-integration-mapper', description: "Integration Mapper — typed output agent (draft spec).", systemPrompt: `You are Integration Mapper. Match agent pains to @agentskit/integrations. Output: Integration map typed per agent.Draft sections with citations from input. Gaps for missing facts.NEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.${UNTRUSTED_CONTENT_DIRECTIVE}Call submit_integration_mapper exactly once. Stop.`, tools: ['submit_integration_mapper'],}export function createEcosystemIntegrationMapperAgent(config: EcosystemIntegrationMapperConfig) { const submit = (): ToolDefinition => defineZodTool({ name: 'submit_integration_mapper', description: 'Submit result. Once.', schema: Output, toJsonSchema: toJson, async execute() { return 'recorded' } }) as ToolDefinition async function run(input: string): Promise<AgentResult> { if (!input?.trim()) throw new Error('ecosystem-integration-mapper requires non-empty input') const result = await invokeStructured({ adapter: config.adapter, tool: submit(), task: `INPUT:\n${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: 'ecosystem-integration-mapper', run, asHandle() { return { name: 'ecosystem-integration-mapper', 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: 'ecosystem-integration-mapper', cases: [ { input: 'Complete input for Integration Mapper: Match agent pains to @agentskit/integrations. 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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