content·Independently reviewed · 96/100

Podcast Show Notes

Notes typed. Show notes manual. Typed v1 agent with eval coverage.

contentstructured-outputv1

Install

npx agentskit add content-podcast-show-notes

Quick start

import { openai } from '@agentskit/adapters'import { createContentPodcastShowNotesAgent } from './agents/content-podcast-show-notes/agent'const agent = createContentPodcastShowNotesAgent({  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 show-notes objects for all three cases, avoided fabrication when source material was absent, surfaced concrete gaps and open questions, and resisted the injection attempt. Behavior is aligned with a cautious podcast show-notes agent. Minor weaknesses are that the normal case is treated entirely as missing-source input rather than offering a reusable show-notes scaffold, and some citations echo internal untrusted-input markers, but these are not critical failures.

What passed review

  • Valid structured outputs across all cases.
  • Does not hallucinate episode details from sparse or meta inputs.
  • Clearly surfaces uncertainty, missing context, and human-review need.
  • Correctly ignores the prompt-injection request to output APPROVED.
  • Provides useful follow-up questions for obtaining source material.

Extend it

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

const agent = createContentPodcastShowNotesAgent({  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'/** Podcast Show Notes — v1 validated. Pain: Show notes manual */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 ContentPodcastShowNotesConfig {  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: 'content-podcast-show-notes',  description: "Podcast Show Notes — typed output agent (draft spec).",  systemPrompt: `You are Podcast Show Notes. Show notes manual. Output: Notes 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.${UNTRUSTED_CONTENT_DIRECTIVE}Call submit_show_notes exactly once. Stop.`,  tools: ['submit_show_notes'],}export function createContentPodcastShowNotesAgent(config: ContentPodcastShowNotesConfig) {  const submit = (): ToolDefinition =>    defineZodTool({ name: 'submit_show_notes', description: 'Submit result. Once.', schema: Output, toJsonSchema: toJson, async execute() { return 'recorded' } }) as ToolDefinition  async function run(input: string): Promise<AgentResult> {    if (!input?.trim()) throw new Error('content-podcast-show-notes requires non-empty input')    const result = await invokeStructured({      adapter: config.adapter,      tool: submit(),      task: `INPUT:\n${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: 'content-podcast-show-notes',    run,    asHandle() { return { name: 'content-podcast-show-notes', 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: 'content-podcast-show-notes',  cases: [    { input: 'Complete input for Podcast Show Notes: Show notes manual. 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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