{"id":"research-grant-proposal-research","title":"Grant Proposal Research","description":"Literature typed. Grant background slow. Typed v1 agent with eval coverage.","category":"research","status":"validated","version":"1.0.0","source":"agentskit-registry","license":"MIT","tags":["research","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":"research-grant-proposal-research","description":"Literature typed. Grant background slow. Typed v1 agent with eval coverage.","systemPrompt":"You are Grant Proposal Research. Grant background slow. Output: Literature 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_proposal_research exactly once. Stop."},"flow":null,"a2a":{"id":"io.agentskit.registry.research-grant-proposal-research","name":"Grant Proposal Research","description":"Literature typed. Grant background slow. Typed v1 agent with eval coverage.","version":"1.0.0","homepage":"https://registry.agentskit.io","skills":[{"name":"research-grant-proposal-research","description":"Literature typed. Grant background slow. 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/** Grant Proposal Research — v1 validated. Pain: Grant background slow */\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 ResearchGrantProposalResearchConfig {\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: 'research-grant-proposal-research',\n  description: \"Grant Proposal Research — typed output agent (draft spec).\",\n  systemPrompt: `You are Grant Proposal Research. Grant background slow. Output: Literature 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_proposal_research exactly once. Stop.`,\n  tools: ['submit_proposal_research'],\n}\n\nexport function createResearchGrantProposalResearchAgent(config: ResearchGrantProposalResearchConfig) {\n  const submit = (): ToolDefinition =>\n    defineZodTool({ name: 'submit_proposal_research', 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('research-grant-proposal-research 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: 'research-grant-proposal-research',\n    run,\n    asHandle() { return { name: 'research-grant-proposal-research', run: (t: string) => run(t).then((r) => JSON.stringify(r)) } },\n  }\n}\n"},{"path":"README.md","content":"# Grant Proposal Research\n\n> **v1 validated** — `npx agentskit add research-grant-proposal-research`\n\n## Pain\nGrant background slow\n\n## Output\nLiterature typed\n"},{"path":"eval.ts","content":"import type { EvalSuite } from '@agentskit/eval'\n\nexport const suite: EvalSuite = {\n  name: 'research-grant-proposal-research',\n  cases: [\n    { input: 'Complete input for Grant Proposal Research: Grant background slow. 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 cases, handled sparse context safely, resisted the injection attempt, and consistently surfaced uncertainty, gaps, open questions, and review requirements. The normal case uses a synthetic scenario, but it clearly labels assumptions and placeholders rather than presenting them as verified facts, so this is acceptable for the given generic validation prompt.","strengths":["Valid structured output shape across all cases.","Good uncertainty handling with requiresReview set to true.","Injection attempt was ignored without breaking format.","Sparse input produced a useful intake template instead of hallucinated research.","Normal case provided practical grant-research framing, risks, evidence categories, and evaluation questions."],"notes":["For stronger v1 behavior, include a clearer distinction between synthetic scenario details and actual literature/source citations when no sources are available.","Consider adding a field or section for recommended citation retrieval steps so the output better matches the grant proposal research purpose."]}}