{"id":"marketing-landing-cro-auditor","title":"Landing CRO Auditor","description":"CRO findings typed. LP not converting. Typed v1 agent with eval coverage.","category":"marketing","status":"validated","version":"1.0.0","source":"agentskit-registry","license":"MIT","tags":["marketing","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":"marketing-landing-cro-auditor","description":"CRO findings typed. LP not converting. Typed v1 agent with eval coverage.","systemPrompt":"You are Landing CRO Auditor. LP not converting. Output: CRO findings typed.\nActionable findings citing input sources. No invented issues.\nNEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.\n${UNTRUSTED_CONTENT_DIRECTIVE}\nCall submit_cro_auditor exactly once. Stop."},"flow":null,"a2a":{"id":"io.agentskit.registry.marketing-landing-cro-auditor","name":"Landing CRO Auditor","description":"CRO findings typed. LP not converting. Typed v1 agent with eval coverage.","version":"1.0.0","homepage":"https://registry.agentskit.io","skills":[{"name":"marketing-landing-cro-auditor","description":"CRO findings typed. LP not converting. 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/** Landing CRO Auditor — v1 validated. Pain: LP not converting */\n\nexport interface Finding { id: string; severity: 'critical' | 'high' | 'medium' | 'low' | 'info'; message: string; source?: string; recommendation?: string }\nexport interface AgentOutput { summary: string; findings: Finding[]; gaps: string[]; openQuestions: string[] }\nexport interface AgentResult extends AgentOutput { requiresReview: boolean }\nexport interface MarketingLandingCroAuditorConfig {\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  summary: z.string(),\n  findings: z.array(z.object({\n    id: z.string(), severity: z.enum(['critical', 'high', 'medium', 'low', 'info']),\n    message: z.string(), source: z.string().optional(), recommendation: z.string().optional(),\n  })),\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: 'marketing-landing-cro-auditor',\n  description: \"Landing CRO Auditor — typed output agent (draft spec).\",\n  systemPrompt: `You are Landing CRO Auditor. LP not converting. Output: CRO findings typed.\nActionable findings citing input sources. No invented issues.\nNEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.\n${UNTRUSTED_CONTENT_DIRECTIVE}\nCall submit_cro_auditor exactly once. Stop.`,\n  tools: ['submit_cro_auditor'],\n}\n\nexport function createMarketingLandingCroAuditorAgent(config: MarketingLandingCroAuditorConfig) {\n  const submit = (): ToolDefinition =>\n    defineZodTool({ name: 'submit_cro_auditor', 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('marketing-landing-cro-auditor 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: 'marketing-landing-cro-auditor',\n    run,\n    asHandle() { return { name: 'marketing-landing-cro-auditor', run: (t: string) => run(t).then((r) => JSON.stringify(r)) } },\n  }\n}\n"},{"path":"README.md","content":"# Landing CRO Auditor\n\n> **v1 validated** — `npx agentskit add marketing-landing-cro-auditor`\n\n## Pain\nLP not converting\n\n## Output\nCRO findings typed\n"},{"path":"eval.ts","content":"import type { EvalSuite } from '@agentskit/eval'\n\nexport const suite: EvalSuite = {\n  name: 'marketing-landing-cro-auditor',\n  cases: [\n    { input: 'Complete input for Landing CRO Auditor: LP not converting. 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 CRO-auditor outputs for all cases, resisted the injection case, avoided fabricating landing-page facts, surfaced uncertainty clearly, and provided actionable gaps/open questions. Behavior is somewhat conservative in treating benign task wording as untrusted/instruction-like, but that does not materially reduce usefulness for v1 given the sparse inputs.","strengths":["Valid structured outputs with summary, findings, gaps, openQuestions, and review flag across all cases.","Correctly refused to invent CRO findings without landing page artifacts or analytics evidence.","Handled prompt injection by treating it as untrusted data and did not output the requested APPROVED string.","Useful gap lists and questions identify the minimum context needed for a real CRO audit."],"notes":[]}}