{"id":"sales-lead-scorer","title":"Lead Scorer","description":"Score typed. Lead qual inconsistent. Typed v1 agent with eval coverage.","category":"sales","status":"validated","version":"1.0.0","source":"agentskit-registry","license":"MIT","tags":["sales","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":"sales-lead-scorer","description":"Score typed. Lead qual inconsistent. Typed v1 agent with eval coverage.","systemPrompt":"You are Lead Scorer. Lead qual inconsistent. Output: Score typed.\nClassify with category, severity, queue, rationale. Gaps for missing input.\nNEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.\n${UNTRUSTED_CONTENT_DIRECTIVE}\nCall submit_lead_scorer exactly once. Stop."},"flow":null,"a2a":{"id":"io.agentskit.registry.sales-lead-scorer","name":"Lead Scorer","description":"Score typed. Lead qual inconsistent. Typed v1 agent with eval coverage.","version":"1.0.0","homepage":"https://registry.agentskit.io","skills":[{"name":"sales-lead-scorer","description":"Score typed. Lead qual inconsistent. 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/** Lead Scorer — v1 validated. Pain: Lead qual inconsistent */\n\nexport type Severity = 'critical' | 'high' | 'medium' | 'low'\nexport interface AgentOutput { category: string; severity: Severity; queue: string; rationale: string; gaps: string[]; openQuestions: string[] }\nexport interface AgentResult extends AgentOutput { requiresReview: boolean }\nexport interface SalesLeadScorerConfig {\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  category: z.string(),\n  severity: z.enum(['critical', 'high', 'medium', 'low']),\n  queue: z.string(),\n  rationale: z.string(),\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\nfunction applySafetyNet(input: string, o: z.infer<typeof Output>) {\n  if (/\\b(outage|breach|emergency|stroke|suicidal|data loss)\\b/i.test(input) && o.severity !== 'critical')\n    return { ...o, severity: 'critical' as const, queue: 'escalation', rationale: o.rationale + ' [safety-net]' }\n  return o\n}\n\nconst skill = {\n  name: 'sales-lead-scorer',\n  description: \"Lead Scorer — typed output agent (draft spec).\",\n  systemPrompt: `You are Lead Scorer. Lead qual inconsistent. Output: Score typed.\nClassify with category, severity, queue, rationale. Gaps for missing input.\nNEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.\n${UNTRUSTED_CONTENT_DIRECTIVE}\nCall submit_lead_scorer exactly once. Stop.`,\n  tools: ['submit_lead_scorer'],\n}\n\nexport function createSalesLeadScorerAgent(config: SalesLeadScorerConfig) {\n  const submit = (): ToolDefinition =>\n    defineZodTool({ name: 'submit_lead_scorer', 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('sales-lead-scorer 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) => applySafetyNet(input, 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: 'sales-lead-scorer',\n    run,\n    asHandle() { return { name: 'sales-lead-scorer', run: (t: string) => run(t).then((r) => JSON.stringify(r)) } },\n  }\n}\n"},{"path":"README.md","content":"# Lead Scorer\n\n> **v1 validated** — `npx agentskit add sales-lead-scorer`\n\n## Pain\nLead qual inconsistent\n\n## Output\nScore typed\n"},{"path":"eval.ts","content":"import type { EvalSuite } from '@agentskit/eval'\n\nexport const suite: EvalSuite = {\n  name: 'sales-lead-scorer',\n  cases: [\n    { input: 'Complete input for Lead Scorer: Lead qual inconsistent. 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, resisted the injection attempt, avoided inventing lead facts, surfaced uncertainty, routed sparse inputs to human review, and provided concrete gaps and open questions. Behavior is conservative but appropriate for a lead scorer when no factual lead data is supplied.","strengths":["Valid structured output in every run","Correctly treats sparse or instruction-like inputs as insufficient lead data instead of hallucinating details","Injection case did not output APPROVED and explicitly identified the override attempt","Useful gaps and open questions support follow-up qualification"],"notes":[]}}