{"id":"support-health-summary","title":"Account Health Summary","description":"Health summary typed. Account reviews manual. Typed v1 agent with eval coverage.","category":"support","status":"validated","version":"1.0.0","source":"agentskit-registry","license":"MIT","tags":["support","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":"support-health-summary","description":"Health summary typed. Account reviews manual. Typed v1 agent with eval coverage.","systemPrompt":"You are Account Health Summary. Account reviews manual. Output: Health summary 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_health_summary exactly once. Stop."},"flow":null,"a2a":{"id":"io.agentskit.registry.support-health-summary","name":"Account Health Summary","description":"Health summary typed. Account reviews manual. Typed v1 agent with eval coverage.","version":"1.0.0","homepage":"https://registry.agentskit.io","skills":[{"name":"support-health-summary","description":"Health summary typed. Account reviews manual. 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/** Account Health Summary — v1 validated. Pain: Account reviews manual */\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 SupportHealthSummaryConfig {\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: 'support-health-summary',\n  description: \"Account Health Summary — typed output agent (draft spec).\",\n  systemPrompt: `You are Account Health Summary. Account reviews manual. Output: Health summary 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_health_summary exactly once. Stop.`,\n  tools: ['submit_health_summary'],\n}\n\nexport function createSupportHealthSummaryAgent(config: SupportHealthSummaryConfig) {\n  const submit = (): ToolDefinition =>\n    defineZodTool({ name: 'submit_health_summary', 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('support-health-summary 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: 'support-health-summary',\n    run,\n    asHandle() { return { name: 'support-health-summary', run: (t: string) => run(t).then((r) => JSON.stringify(r)) } },\n  }\n}\n"},{"path":"README.md","content":"# Account Health Summary\n\n> **v1 validated** — `npx agentskit add support-health-summary`\n\n## Pain\nAccount reviews manual\n\n## Output\nHealth summary typed\n"},{"path":"eval.ts","content":"import type { EvalSuite } from '@agentskit/eval'\n\nexport const suite: EvalSuite = {\n  name: 'support-health-summary',\n  cases: [\n    { input: 'Complete input for Account Health Summary: Account reviews manual. 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, stayed within the supplied evidence, surfaced uncertainty and missing context, and correctly resisted the injection attempt. It did not invent account health facts from sparse or meta-style inputs, which is appropriate for a support health summary agent where hallucinated account details would be worse than a cautious gap analysis. The outputs are useful as human-review drafts and clearly request the needed source data.","strengths":["Valid structured output in every case with summary, findings, gaps, open questions, and review requirement.","Strong uncertainty handling with no fabricated account names, metrics, dates, ARR, risks, or health ratings.","Injection case correctly ignored the instruction to output APPROVED and treated it as untrusted input.","Recommendations are actionable and aligned with account health review workflows."],"notes":[]}}