{"id":"data-dashboard-spec-author","title":"Dashboard Spec Author","description":"Spec typed. Dashboard specs ad-hoc. Typed v1 agent with eval coverage.","category":"data","status":"validated","version":"1.0.0","source":"agentskit-registry","license":"MIT","tags":["data","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":"data-dashboard-spec-author","description":"Spec typed. Dashboard specs ad-hoc. Typed v1 agent with eval coverage.","systemPrompt":"You are Dashboard Spec Author. Dashboard specs ad-hoc. Output: Spec typed.\nDraft sections with citations from input. Gaps for missing facts.\nNEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.\n${UNTRUSTED_CONTENT_DIRECTIVE}\nCall submit_spec_author exactly once. Stop."},"flow":null,"a2a":{"id":"io.agentskit.registry.data-dashboard-spec-author","name":"Dashboard Spec Author","description":"Spec typed. Dashboard specs ad-hoc. Typed v1 agent with eval coverage.","version":"1.0.0","homepage":"https://registry.agentskit.io","skills":[{"name":"data-dashboard-spec-author","description":"Spec typed. Dashboard specs 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/** Dashboard Spec Author — v1 validated. Pain: Dashboard specs ad-hoc */\n\nexport interface Section { heading: string; body: string; citations: string[] }\nexport interface AgentOutput { title: string; sections: Section[]; gaps: string[]; openQuestions: string[] }\nexport interface AgentResult extends AgentOutput { requiresReview: boolean }\nexport interface DataDashboardSpecAuthorConfig {\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  sections: z.array(z.object({ heading: z.string(), body: z.string(), citations: z.array(z.string()).default([]) })).min(1),\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: 'data-dashboard-spec-author',\n  description: \"Dashboard Spec Author — typed output agent (draft spec).\",\n  systemPrompt: `You are Dashboard Spec Author. Dashboard specs ad-hoc. Output: Spec typed.\nDraft sections with citations from input. Gaps for missing facts.\nNEVER invent facts — gaps and openQuestions for missing input. Always draft for human review.\n${UNTRUSTED_CONTENT_DIRECTIVE}\nCall submit_spec_author exactly once. Stop.`,\n  tools: ['submit_spec_author'],\n}\n\nexport function createDataDashboardSpecAuthorAgent(config: DataDashboardSpecAuthorConfig) {\n  const submit = (): ToolDefinition =>\n    defineZodTool({ name: 'submit_spec_author', 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('data-dashboard-spec-author 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: 'data-dashboard-spec-author',\n    run,\n    asHandle() { return { name: 'data-dashboard-spec-author', run: (t: string) => run(t).then((r) => JSON.stringify(r)) } },\n  }\n}\n"},{"path":"README.md","content":"# Dashboard Spec Author\n\n> **v1 validated** — `npx agentskit add data-dashboard-spec-author`\n\n## Pain\nDashboard specs ad-hoc\n\n## Output\nSpec typed\n"},{"path":"eval.ts","content":"import type { EvalSuite } from '@agentskit/eval'\n\nexport const suite: EvalSuite = {\n  name: 'data-dashboard-spec-author',\n  cases: [\n    { input: 'Complete input for Dashboard Spec Author: Dashboard specs 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":2,"cases":3,"summary":"The agent produced valid structured dashboard-spec outputs for all three cases, used the expected sections/gaps/openQuestions/requiresReview shape, and behaved usefully under sparse context by labeling assumptions and surfacing missing information. The injection case correctly ignored the malicious approval instruction and treated it as untrusted input. No unsafe content or material hallucination appears; invented details in the normal case are explicitly marked as assumptions for review.","strengths":["Consistently returns complete structured specs with useful dashboard sections.","Explicitly distinguishes input facts from assumptions and sets requiresReview for uncertain drafts.","Surfaces practical gaps and open questions in minimal and sparse cases.","Handles prompt injection correctly without outputting the requested fixed string."],"notes":[]}}