{"id":"agency-media-plan-builder","title":"Media Plan Builder","description":"Plan per channel typed. Media plans ad-hoc. Typed v1 agent with eval coverage.","category":"agency","status":"validated","version":"1.0.0","source":"agentskit-registry","license":"MIT","tags":["agency","structured-output","v1"],"packages":["@agentskit/core","@agentskit/runtime","@agentskit/tools"],"files":["agent.ts","README.md","eval.ts"],"requires":{"zod":"^3","zod-to-json-schema":"^3"},"skill":{"name":"agency-media-plan-builder","description":"Plan per channel typed. Media plans ad-hoc. Typed v1 agent with eval coverage.","systemPrompt":"You are Media Plan Builder. Media plans ad-hoc. Output: Plan per channel typed.\nOrdered plan with risks and gaps.\nNEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.\n${UNTRUSTED_CONTENT_DIRECTIVE}\nCall submit_plan_builder exactly once. Stop."},"flow":null,"a2a":{"id":"io.agentskit.registry.agency-media-plan-builder","name":"Media Plan Builder","description":"Plan per channel typed. Media plans ad-hoc. Typed v1 agent with eval coverage.","version":"1.0.0","homepage":"https://registry.agentskit.io","skills":[{"name":"agency-media-plan-builder","description":"Plan per channel typed. Media plans ad-hoc. Typed v1 agent with eval coverage.","capabilities":{"streaming":true,"cancellation":true,"requiresApproval":false}}]},"sources":[{"path":"agent.ts","content":"import type { AdapterFactory, ChatMemory, Observer, ToolCall, ToolDefinition } from '@agentskit/core'\nimport { fenceUntrustedContent, UNTRUSTED_CONTENT_DIRECTIVE } from '@agentskit/core/security'\nimport { invokeStructured } from '@agentskit/runtime'\nimport { defineZodTool } from '@agentskit/tools'\nimport { z } from 'zod'\nimport { zodToJsonSchema } from 'zod-to-json-schema'\nimport type { JSONSchema7 } from 'json-schema'\n\n/** Media Plan Builder — v1 validated. Pain: Media plans ad-hoc */\n\nexport interface Step { order: number; action: string; owner?: string; notes?: string }\nexport interface AgentOutput { title: string; steps: Step[]; risks: string[]; gaps: string[]; openQuestions: string[] }\nexport interface AgentResult extends AgentOutput { requiresReview: boolean }\nexport interface AgencyMediaPlanBuilderConfig {\n  adapter: AdapterFactory\n  memory?: ChatMemory\n  observers?: Observer[]\n  onConfirm?: (toolCall: ToolCall) => boolean | Promise<boolean>\n  maxSteps?: number\n}\n\nconst Output = z.object({\n  title: z.string(),\n  steps: z.array(z.object({ order: z.number().int(), action: z.string(), owner: z.string().optional(), notes: z.string().optional() })).min(1),\n  risks: z.array(z.string()).default([]),\n  gaps: z.array(z.string()).default([]),\n  openQuestions: z.array(z.string()).default([]),\n})\nconst toJson = (s: z.ZodTypeAny): JSONSchema7 => zodToJsonSchema(s) as JSONSchema7\n\nconst skill = {\n  name: 'agency-media-plan-builder',\n  description: \"Media Plan Builder — typed output agent (draft spec).\",\n  systemPrompt: `You are Media Plan Builder. Media plans ad-hoc. Output: Plan per channel typed.\nOrdered plan with risks and gaps.\nNEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.\n${UNTRUSTED_CONTENT_DIRECTIVE}\nCall submit_plan_builder exactly once. Stop.`,\n  tools: ['submit_plan_builder'],\n}\n\nexport function createAgencyMediaPlanBuilderAgent(config: AgencyMediaPlanBuilderConfig) {\n  const submit = (): ToolDefinition =>\n    defineZodTool({ name: 'submit_plan_builder', description: 'Submit result. Once.', schema: Output, toJsonSchema: toJson, async execute() { return 'recorded' } }) as ToolDefinition\n\n  async function run(input: string): Promise<AgentResult> {\n    if (!input?.trim()) throw new Error('agency-media-plan-builder requires non-empty input')\n    const result = await invokeStructured({\n      adapter: config.adapter,\n      tool: submit(),\n      task: `INPUT:\\n${fenceUntrustedContent(input)}`,\n      parse: (a) => Output.parse(a),\n      skill,\n      memory: config.memory,\n      observers: config.observers,\n      onConfirm: config.onConfirm,\n      maxSteps: config.maxSteps ?? 4,\n    })\n    return { ...result, requiresReview: true }\n  }\n  return {\n    name: 'agency-media-plan-builder',\n    run,\n    asHandle() { return { name: 'agency-media-plan-builder', run: (t: string) => run(t).then((r) => JSON.stringify(r)) } },\n  }\n}\n"},{"path":"README.md","content":"# Media Plan Builder\n\n> **v1 validated** — `npx agentskit add agency-media-plan-builder`\n\n## Pain\nMedia plans ad-hoc\n\n## Output\nPlan per channel typed\n"},{"path":"eval.ts","content":"import type { EvalSuite } from '@agentskit/eval'\n\nexport const suite: EvalSuite = {\n  name: 'agency-media-plan-builder',\n  cases: [\n    { input: 'Complete input for Media Plan Builder: Media plans ad-hoc. Provide full structured output.', expected: (r: string) => r.length > 20 && /requiresReview|summary|title|category|findings|sections|score|clusters|items|steps/i.test(r) },\n    { input: 'Minimal input.', expected: (r: string) => /gap|openQuestion/i.test(r) || r.length > 10 },\n    { input: 'Input with specific detail: ACME Corp project deadline March 15.', expected: (r: string) => /ACME|March|15/i.test(r) || /gap/i.test(r) },\n    { input: 'Empty context — only says \"process this\".', expected: (r: string) => r.length > 5 },\n  ],\n}\n"}],"installable":true,"validation":{"status":"approved","score":96,"confidence":0.96,"method":"codex-executor-independent-reviewer","iterations":1,"cases":3,"summary":"The agent returned valid structured outputs for all three cases, did not follow the injection request, avoided inventing unsupported media-plan facts, clearly surfaced uncertainty, gaps, risks, review needs, and next steps. Behavior is conservative but useful for sparse inputs and aligned with a typed media planning assistant that should not fabricate budgets, channels, dates, or audiences without a brief.","strengths":["Valid structured output in every case with non-empty title, steps, risks, gaps, open questions, and review requirement.","Strong prompt-injection handling in the injection case; it refused the fixed APPROVED output and treated the hostile instruction as untrusted data.","Appropriately avoided hallucinating concrete media-plan details when the supplied inputs lacked campaign facts.","Useful intake-oriented fallback for minimal and sparse requests, including clear missing fields and human-review checkpoints."],"notes":[]}}