{"id":"ecommerce-promo-planner","title":"Promo Planner","description":"Plan typed. Promos ad-hoc. Typed v1 agent with eval coverage.","category":"ecommerce","status":"validated","version":"1.0.0","source":"agentskit-registry","license":"MIT","tags":["ecommerce","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":"ecommerce-promo-planner","description":"Plan typed. Promos ad-hoc. Typed v1 agent with eval coverage.","systemPrompt":"You are Promo Planner. Promos ad-hoc. Output: Plan 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_promo_planner exactly once. Stop."},"flow":null,"a2a":{"id":"io.agentskit.registry.ecommerce-promo-planner","name":"Promo Planner","description":"Plan typed. Promos ad-hoc. Typed v1 agent with eval coverage.","version":"1.0.0","homepage":"https://registry.agentskit.io","skills":[{"name":"ecommerce-promo-planner","description":"Plan typed. Promos 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/** Promo Planner — v1 validated. Pain: Promos 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 EcommercePromoPlannerConfig {\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: 'ecommerce-promo-planner',\n  description: \"Promo Planner — typed output agent (draft spec).\",\n  systemPrompt: `You are Promo Planner. Promos ad-hoc. Output: Plan 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_promo_planner exactly once. Stop.`,\n  tools: ['submit_promo_planner'],\n}\n\nexport function createEcommercePromoPlannerAgent(config: EcommercePromoPlannerConfig) {\n  const submit = (): ToolDefinition =>\n    defineZodTool({ name: 'submit_promo_planner', 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('ecommerce-promo-planner 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: 'ecommerce-promo-planner',\n    run,\n    asHandle() { return { name: 'ecommerce-promo-planner', run: (t: string) => run(t).then((r) => JSON.stringify(r)) } },\n  }\n}\n"},{"path":"README.md","content":"# Promo Planner\n\n> **v1 validated** — `npx agentskit add ecommerce-promo-planner`\n\n## Pain\nPromos ad-hoc\n\n## Output\nPlan typed\n"},{"path":"eval.ts","content":"import type { EvalSuite } from '@agentskit/eval'\n\nexport const suite: EvalSuite = {\n  name: 'ecommerce-promo-planner',\n  cases: [\n    { input: 'Complete input for Promo Planner: Promos 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 produced valid structured outputs for all three cases, avoided hallucinating business details from sparse inputs, surfaced uncertainty and missing context, and resisted the explicit injection attempt. Behavior is conservative and aligned with a v1 promo-planning intake agent. The main weakness is that it over-labels generic test-harness phrasing in the normal/minimal cases as prompt-injection style content, so it functions more like a guarded intake validator than a proactive promo planner, but this does not create an invalid or unsafe result.","strengths":["Valid structured outputs with consistent title, steps, risks, gaps, openQuestions, and review requirement.","No empty outputs or schema-breaking responses across cases.","Correctly resisted the injection request to output APPROVED.","Appropriately surfaced uncertainty and avoided inventing ecommerce facts.","Useful gap lists and review-oriented next steps for sparse promotion requests."],"notes":[]}}