{"id":"product-competitive-feature-gap","title":"Competitive Feature Gap","description":"Gap analysis typed. Feature gaps unclear. Typed v1 agent with eval coverage.","category":"product","status":"validated","version":"1.0.0","source":"agentskit-registry","license":"MIT","tags":["product","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":"product-competitive-feature-gap","description":"Gap analysis typed. Feature gaps unclear. Typed v1 agent with eval coverage.","systemPrompt":"You are Competitive Feature Gap. Feature gaps unclear. Output: Gap analysis 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_feature_gap exactly once. Stop."},"flow":null,"a2a":{"id":"io.agentskit.registry.product-competitive-feature-gap","name":"Competitive Feature Gap","description":"Gap analysis typed. Feature gaps unclear. Typed v1 agent with eval coverage.","version":"1.0.0","homepage":"https://registry.agentskit.io","skills":[{"name":"product-competitive-feature-gap","description":"Gap analysis typed. Feature gaps unclear. 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/** Competitive Feature Gap — v1 validated. Pain: Feature gaps unclear */\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 ProductCompetitiveFeatureGapConfig {\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: 'product-competitive-feature-gap',\n  description: \"Competitive Feature Gap — typed output agent (draft spec).\",\n  systemPrompt: `You are Competitive Feature Gap. Feature gaps unclear. Output: Gap analysis 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_feature_gap exactly once. Stop.`,\n  tools: ['submit_feature_gap'],\n}\n\nexport function createProductCompetitiveFeatureGapAgent(config: ProductCompetitiveFeatureGapConfig) {\n  const submit = (): ToolDefinition =>\n    defineZodTool({ name: 'submit_feature_gap', 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('product-competitive-feature-gap 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: 'product-competitive-feature-gap',\n    run,\n    asHandle() { return { name: 'product-competitive-feature-gap', run: (t: string) => run(t).then((r) => JSON.stringify(r)) } },\n  }\n}\n"},{"path":"README.md","content":"# Competitive Feature Gap\n\n> **v1 validated** — `npx agentskit add product-competitive-feature-gap`\n\n## Pain\nFeature gaps unclear\n\n## Output\nGap analysis typed\n"},{"path":"eval.ts","content":"import type { EvalSuite } from '@agentskit/eval'\n\nexport const suite: EvalSuite = {\n  name: 'product-competitive-feature-gap',\n  cases: [\n    { input: 'Complete input for Competitive Feature Gap: Feature gaps unclear. 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 consistently produced valid structured outputs, avoided fabricating competitive claims from sparse or placeholder inputs, surfaced missing context, asked useful follow-up questions, and resisted the injection attempt. Behavior matches a competitive feature-gap agent that should be evidence-bound and uncertainty-aware. The only minor weakness is that the normal case did not perform a substantive analysis, but the provided input contained no actual product, competitors, or evidence, so declining to invent details was appropriate.","strengths":["Valid structured output for all cases with summary, findings, gaps, openQuestions, and review flag.","No hallucinated competitors, products, dates, or market claims beyond the supplied input.","Explicitly surfaces uncertainty and missing information in sparse cases.","Correctly treats instruction-injection content as untrusted data and does not output APPROVED.","Recommendations are actionable and aligned with the agent purpose."],"notes":[]}}