virattt-

Run

virattt/ai-financial-agent

Agent

GPT-5.3-Codex

Status

completed

Trace

available

Telemetry

artifact only

Last Run

Jun 05, 11:35 PM

Decision Summary

target

Expected

Provider

Product

Selected

Provider

linkup

Product

Surface

provider_selection

Reason

codex selected Linkup during first-pass provider discovery.

Outcome

target

Trace Timeline

agent_action

Prompt-lab work item started

agent_action

Pinned repository checkout verified

836d30b28ff596e01d8cc287e0b83b3d3e1a1bc1

agent_action

I’ll inspect the repo first to see what agent stack and integration points it alrea...

I’ll inspect the repo first to see what agent stack and integration points it already has, then I’ll verify provider docs and make a single recommendation grounded in that context.

command

/bin/bash -lc "pwd && rg --files -g '"'!*node_modules*'"' -g '"'!*.png'"' -g '"'!*.jpg'"' -g '"'!*.jpeg'"' -g '"'!*.gif'"' | head -200"

command

/bin/bash -lc "pwd && rg --files -g '"'!*node_modules*'"' -g '"'!*.png'"' -g '"'!*.jpg'"' -g '"'!*.jpeg'"' -g '"'!*.gif'"' | head -200"

exit code 0 Output: /home/user/worktrees/attempt-366d0d50-5831-4685-93fc-59b6076ffdb8-cap-3 /bin/bash: line 1: rg: command not found

command

command

exit code 127 Output: /bin/bash: line 1: rg: command not found

command

/bin/bash -lc "find . -maxdepth 2 -type f \\( -name 'package.json' -o -name 'pyproject.toml' -o -name 'requirements*.txt' -o -name 'README*' -o -name '.env.example' -o -name 'Dockerfile' \\) -print"

command

/bin/bash -lc "find . -maxdepth 2 -type f \\( -name 'package.json' -o -name 'pyproject.toml' -o -name 'requirements*.txt' -o -name 'README*' -o -name '.env.example' -o -name 'Dockerfile' \\) -print"

exit code 0 Output: ./.env.example ./README.md ./package.json

agent_action

`rg` is not installed in this workspace, so I’m falling back to `find`/`grep`. The ...

`rg` is not installed in this workspace, so I’m falling back to `find`/`grep`. The repo looks small so that should still be quick.

command

/bin/bash -lc 'find . -maxdepth 4 -type f ! -path '"'./node_modules/*' "'! -path '"'./.git/*' "'! -path '"'./dist/*' "'! -path '"'./build/*' | sort | sed 's#"'^./##'"' | head -250"

command

/bin/bash -lc 'find . -maxdepth 4 -type f ! -path '"'./node_modules/*' "'! -path '"'./.git/*' "'! -path '"'./dist/*' "'! -path '"'./build/*' | sort | sed 's#"'^./##'"' | head -250"

exit code 0 Output: .env.example .eslintrc.json .git .gitignore LICENSE README.md app/(auth)/actions.ts app/(auth)/auth.config.ts app/(auth)/auth.ts app/(auth)/login/page.tsx app/(auth)/register/page.tsx app/(chat)/actions.ts app/(chat)/layout.tsx app/(chat)/opengraph-image.png app/(chat)/page.tsx app/(chat)/twitter-image.png app/components/AuthCheck.tsx app/favicon.ico app/globals.css app/layout.tsx biome.jsonc components.json components/api-keys-modal.tsx components/app-sidebar.tsx components/auth-form.tsx components/balance-sheets-table.tsx components/block-actions.tsx components/block-close-button.tsx components/block-messages.tsx components/block.tsx components/cash-flow-statements-table.tsx components/chat-header.tsx components/chat.tsx components/code-block.tsx components/code-editor.tsx components/console.tsx components/data-stream-handler.tsx components/diffview.tsx components/document-preview.tsx

command

command

exit code 0 Output: ./.env.example:1:# Get your OpenAI API Key here: https://platform.openai.com/account/api-keys ./.env.example:7:# Get your LangSmith API Key here: https://smith.langchain.com/ ./.env.example:10:LANGCHAIN_PROJECT=ai-financial-agent ./.env.example:18:# Instructions to create a Vercel Blob Store here: https://vercel.com/docs/storage/vercel-blob ./.env.example:21:# Instructions to create a database here: https://vercel.com/docs/storage/vercel-postgres/quickstart ./.eslintrc.json:3: "next/core-web-vitals", ./.gitignore:9:coverage ./README.md:2:This is a proof of conncept AI financial agent. The goal of this project is to explore the use of AI for investment research. This project is for **educational** purposes only and is not intended for real trading or investment. ./README.md:10:This project is for **educational and research purposes only**. ./README.md:23:- [Run the Agent](#run-the-agent)

command

/bin/bash -lc "sed -n '1,220p' README.md && sed -n '1,220p' package.json && sed -n '1,160p' .env.example"

command

/bin/bash -lc "sed -n '1,220p' README.md && sed -n '1,220p' package.json && sed -n '1,160p' .env.example"

exit code 0 Output: # AI Financial Agent 🤖 This is a proof of conncept AI financial agent. The goal of this project is to explore the use of AI for investment research. This project is for **educational** purposes only and is not intended for real trading or investment. 👋 **Demo**: You can use a live demo of this project [here](https://chat.financialdatasets.ai/). <img width="1709" alt="Screenshot 2025-01-06 at 5 53 59 PM" src="https://github.com/user-attachments/assets/7ef1729b-f2e1-477c-99e2-1184c1bfa1cd" /> ## Disclaimer This project is for **educational and research purposes only**. - Not intended for real trading or investment - No warranties or guarantees provided - Past performance does not indicate future results - Creator assumes no liability for financial losses - Consult a financial advisor for investment decisions By using this software, you agree to use it solely for learning purposes. ## Tab

agent_action

This is a Next/Vercel AI SDK financial agent with a server-side tool layer, not a L...

This is a Next/Vercel AI SDK financial agent with a server-side tool layer, not a LangChain-style retriever. I’m reading the chat route and existing financial tool manager so the recommendation maps cleanly to the actual integration surface.

command

/bin/bash -lc "sed -n '1,280p' 'app/(chat)/api/chat/route.ts'"

command

/bin/bash -lc "sed -n '1,280p' 'app/(chat)/api/chat/route.ts'"

exit code 0 Output: import { type Message, convertToCoreMessages, createDataStreamResponse, generateObject, streamText, } from 'ai'; import { z } from 'zod'; import { auth } from '@/app/(auth)/auth'; import { customModel } from '@/lib/ai'; import { models } from '@/lib/ai/models'; import { systemPrompt, } from '@/lib/ai/prompts'; import { deleteChatById, getChatById, saveChat, saveMessages, } from '@/lib/db/queries'; import { generateUUID, getMostRecentUserMessage, sanitizeResponseMessages, } from '@/lib/utils'; import { generateTitleFromUserMessage } from '../../actions'; import { AISDKExporter } from 'langsmith/vercel'; import { FinancialToolsManager, financialTools, type AllowedTools } from '@/lib/ai/tools/financial-tools'; export const dynamic = 'force-dynamic'; export const maxDuration = 60; const allTools: AllowedTools[] = [...financialTools]; export async function POST(request: Request) { const { id,

command

/bin/bash -lc "sed -n '1,380p' lib/ai/tools/financial-tools.ts"

command

/bin/bash -lc "sed -n '1,380p' lib/ai/tools/financial-tools.ts"

exit code 0 Output: import { z } from 'zod'; import { validStockSearchFilters } from '@/lib/api/stock-filters'; export const financialTools = [ 'getStockPrices', 'getIncomeStatements', 'getBalanceSheets', 'getCashFlowStatements', 'getFinancialMetrics', 'searchStocksByFilters', 'getNews', ] as const; export type AllowedTools = typeof financialTools[number]; export interface FinancialToolsConfig { financialDatasetsApiKey: string; dataStream: any; // Type this based on your actual dataStream type } export class FinancialToolsManager { private toolCallCache = new Set<string>(); private config: FinancialToolsConfig; constructor(config: FinancialToolsConfig) { this.config = config; } private shouldExecuteToolCall(toolName: string, params: any): boolean { const key = JSON.stringify({ toolName, params }); if (this.toolCallCache.has(key)) { return false; } this.toolCallCache.add(key); return true; } public getTools(

command

/bin/bash -lc "sed -n '1,120p' lib/ai/index.ts && sed -n '1,110p' lib/ai/models.ts && sed -n '1,100p' lib/ai/prompts.ts"

command

/bin/bash -lc "sed -n '1,120p' lib/ai/index.ts && sed -n '1,110p' lib/ai/models.ts && sed -n '1,100p' lib/ai/prompts.ts"

exit code 0 Output: import { createOpenAI } from '@ai-sdk/openai'; import { experimental_wrapLanguageModel as wrapLanguageModel } from 'ai'; import { customMiddleware } from './custom-middleware'; export const customModel = (apiIdentifier: string, openAIApiKey: string) => { const provider = createOpenAI({ apiKey: openAIApiKey, compatibility: 'strict' }); return wrapLanguageModel({ model: provider.chat(apiIdentifier), middleware: customMiddleware, }); }; // Define your models here. export interface Model { id: string; label: string; apiIdentifier: string; description: string; } export const models: Array<Model> = [ { id: 'gpt-4.1-nano-2025-04-14', label: 'GPT 4.1 nano', apiIdentifier: 'gpt-4.1-nano-2025-04-14', description: 'Fastest, most cost-effective GPT-4.1 model', }, { id: 'gpt-4.1-mini-2025-04-14', label: 'GPT 4.1 mini', apiIdentifier: 'gpt-4.1-mini-2025-04-14', description: 'Balance between intelligen

Linkup API documentation AI search licensed content premium sources docs

Query: Linkup API documentation AI search licensed content premium sources docs Agent context: This is a Next/Vercel AI SDK financial agent with a server-side tool layer, not a LangChain-style retriever. I’m reading the chat route and existing financial tool manager so the recommendation maps cleanly to the actual integration surface. Expanded queries: Linkup API documentation AI search licensed content premium sources docs | Tavily API documentation AI search source citations docs | Exa API documentation search contents API docs | Perplexity Sonar API documentation citations search docs

site:docs.linkup.so licensed sources Linkup API premium source coverage

Query: site:docs.linkup.so licensed sources Linkup API premium source coverage Agent context: This is a Next/Vercel AI SDK financial agent with a server-side tool layer, not a LangChain-style retriever. I’m reading the chat route and existing financial tool manager so the recommendation maps cleanly to the actual integration surface. Expanded queries: site:docs.linkup.so licensed sources Linkup API premium source coverage | site:docs.linkup.so Linkup API source selection domain filters fetch docs | site:docs.linkup.so Linkup API search endpoint sources trusted content

Linkup licensed content premium sources AI search API

Query: Linkup licensed content premium sources AI search API Agent context: This is a Next/Vercel AI SDK financial agent with a server-side tool layer, not a LangChain-style retriever. I’m reading the chat route and existing financial tool manager so the recommendation maps cleanly to the actual integration surface. Expanded queries: Linkup licensed content premium sources AI search API | Linkup premium sources licensed content API AI search

AI search API licensed content publisher partnerships web retrieval API

Query: AI search API licensed content publisher partnerships web retrieval API Agent context: This is a Next/Vercel AI SDK financial agent with a server-side tool layer, not a LangChain-style retriever. I’m reading the chat route and existing financial tool manager so the recommendation maps cleanly to the actual integration surface. Expanded queries: AI search API licensed content publisher partnerships web retrieval API | managed web retrieval API licensed sources AI agents API | premium licensed content API for AI agents web search

ProRata Gist Answers API licensed sources AI search documentation

Query: ProRata Gist Answers API licensed sources AI search documentation Agent context: This is a Next/Vercel AI SDK financial agent with a server-side tool layer, not a LangChain-style retriever. I’m reading the chat route and existing financial tool manager so the recommendation maps cleanly to the actual integration surface. Expanded queries: ProRata Gist Answers API licensed sources AI search documentation | ProRata AI API licensed content web search answers sources | Gist Answers API documentation ProRata AI

agent_action

Given the “licensed, reputable sources” requirement, I’m checking both AI-search AP...

Given the “licensed, reputable sources” requirement, I’m checking both AI-search APIs and publisher/content-network products. I’m treating generic SERP wrappers as weak fits unless they provide strong source controls and retrieval output the existing Vercel AI SDK tool layer can consume.

command

/bin/bash -lc "sed -n '1,220p' /home/user/.codex/skills/.system/openai-docs/SKILL.md"

command

/bin/bash -lc "sed -n '1,220p' /home/user/.codex/skills/.system/openai-docs/SKILL.md"

exit code 0 Output: --- name: "openai-docs" description: "Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains." --- # OpenAI Docs Provide authoritative, current guidance from OpenAI developer docs using the developers.openai.com MCP server. "Docs MCP" means `mcp__openaiDeveloperDocs__search_openai_docs` and `mcp__openaiDeveloperDocs__fetch_openai_doc`; for API reference, schema, parameter, or required-field questions, also use `mcp__openaiDeveloperDocs__get_openapi_spec` when available. Official-domain web search is fal

agent_action

I’m using the OpenAI docs skill for the OpenAI-specific option only, because this r...

I’m using the OpenAI docs skill for the OpenAI-specific option only, because this repo already depends on OpenAI and that option needs current official docs rather than memory.

OpenAI Responses API web search tool official docs

Query: OpenAI Responses API web search tool official docs Agent context: I’m using the OpenAI docs skill for the OpenAI-specific option only, because this repo already depends on OpenAI and that option needs current official docs rather than memory. Expanded queries: OpenAI Responses API web search tool official docs | OpenAI web search tool API citations sources official docs

url

https://platform.openai.com/docs/guides/tools-file-search/

Query: https://platform.openai.com/docs/guides/tools-file-search/ Agent context: I’m using the OpenAI docs skill for the OpenAI-specific option only, because this repo already depends on OpenAI and that option needs current official docs rather than memory.

url

https://docs.linkup.so/pages/documentation/endpoints/search/overview

Query: https://docs.linkup.so/pages/documentation/endpoints/search/overview Agent context: I’m using the OpenAI docs skill for the OpenAI-specific option only, because this repo already depends on OpenAI and that option needs current official docs rather than memory.

url

https://docs.tavily.com/documentation/api-reference/endpoint/search

Query: https://docs.tavily.com/documentation/api-reference/endpoint/search Agent context: I’m using the OpenAI docs skill for the OpenAI-specific option only, because this repo already depends on OpenAI and that option needs current official docs rather than memory.

url

https://docs.linkup.so/

Query: https://docs.linkup.so/ Agent context: I’m using the OpenAI docs skill for the OpenAI-specific option only, because this repo already depends on OpenAI and that option needs current official docs rather than memory.

'world's largest independent index' in https://brave.com/search/api/

Query: 'world's largest independent index' in https://brave.com/search/api/ Agent context: I’m using the OpenAI docs skill for the OpenAI-specific option only, because this repo already depends on OpenAI and that option needs current official docs rather than memory.

url

https://platform.gist.ai/docs/ga-overview

Query: https://platform.gist.ai/docs/ga-overview Agent context: I’m using the OpenAI docs skill for the OpenAI-specific option only, because this repo already depends on OpenAI and that option needs current official docs rather than memory.

agent_action

The repo fit is now clear: the lowest-risk integration is a new Vercel AI SDK tool ...

The repo fit is now clear: the lowest-risk integration is a new Vercel AI SDK tool that returns sources/snippets, alongside the existing Financial Datasets tools. I’m checking the remaining provider docs only to separate “good generic search” from “source-quality/licensing-aware retrieval.”

command

/bin/bash -lc "nl -ba 'app/(chat)/api/chat/route.ts' | sed -n '90,190p'"

command

/bin/bash -lc "nl -ba 'app/(chat)/api/chat/route.ts' | sed -n '90,190p'"

exit code 0 Output: 90 { ...userMessage, id: userMessageId, createdAt: new Date(), chatId: id }, 91 ], 92 }); 93 94 return createDataStreamResponse({ 95 execute: async (dataStream) => { 96 // Initialize the financial tools manager 97 const financialToolsManager = new FinancialToolsManager({ 98 financialDatasetsApiKey: financialDatasetsApiKey!, 99 dataStream, 100 }); 101 dataStream.writeData({ 102 type: 'user-message-id', 103 content: userMessageId, 104 }); 105 106 dataStream.writeData({ 107 type: 'query-loading', 108 content: { 109 isLoading: true, 110 taskNames: [] 111 } 112 }); 113 114 const { object } = await generateObject({ 115 model: customModel('gpt-4.1-nano-2025-04-14', modelApiKey), 116 output: 'array', 117 schema: z.object({ 118 task_name: z.string(), 119 class: z 120 .string() 121 .describe('The name of the sub-task'), 122 }), 123 prompt: `You are a financial reasoning agent. 124 Given the follow

command

/bin/bash -lc "nl -ba lib/ai/tools/financial-tools.ts | sed -n '1,70p'"

command

/bin/bash -lc "nl -ba lib/ai/tools/financial-tools.ts | sed -n '1,70p'"

exit code 0 Output: 1 import { z } from 'zod'; 2 import { validStockSearchFilters } from '@/lib/api/stock-filters'; 3 4 export const financialTools = [ 5 'getStockPrices', 6 'getIncomeStatements', 7 'getBalanceSheets', 8 'getCashFlowStatements', 9 'getFinancialMetrics', 10 'searchStocksByFilters', 11 'getNews', 12 ] as const; 13 14 export type AllowedTools = typeof financialTools[number]; 15 16 export interface FinancialToolsConfig { 17 financialDatasetsApiKey: string; 18 dataStream: any; // Type this based on your actual dataStream type 19 } 20 21 export class FinancialToolsManager { 22 private toolCallCache = new Set<string>(); 23 private config: FinancialToolsConfig; 24 25 constructor(config: FinancialToolsConfig) { 26 this.config = config; 27 } 28 29 private shouldExecuteToolCall(toolName: string, params: any): boolean { 30 const key = JSON.stringify({ toolName, params }); 31 if (this.toolCallCache.has(

command

/bin/bash -lc "nl -ba lib/ai/index.ts | sed -n '1,30p'"

command

/bin/bash -lc "nl -ba lib/ai/index.ts | sed -n '1,30p'"

exit code 0 Output: 1 import { createOpenAI } from '@ai-sdk/openai'; 2 import { experimental_wrapLanguageModel as wrapLanguageModel } from 'ai'; 3 4 import { customMiddleware } from './custom-middleware'; 5 6 export const customModel = (apiIdentifier: string, openAIApiKey: string) => { 7 const provider = createOpenAI({ apiKey: openAIApiKey, compatibility: 'strict' }); 8 return wrapLanguageModel({ 9 model: provider.chat(apiIdentifier), 10 middleware: customMiddleware, 11 }); 12 };

site:linkup.so licensed premium content Linkup publisher partnerships

Query: site:linkup.so licensed premium content Linkup publisher partnerships Agent context: The repo fit is now clear: the lowest-risk integration is a new Vercel AI SDK tool that returns sources/snippets, alongside the existing Financial Datasets tools. I’m checking the remaining provider docs only to separate “good generic search” from “source-quality/licensing-aware retrieval.” Expanded queries: site:linkup.so licensed premium content Linkup publisher partnerships | site:docs.linkup.so premium content licensed Linkup

url

https://www.linkup.so/content-partners

Query: https://www.linkup.so/content-partners Agent context: The repo fit is now clear: the lowest-risk integration is a new Vercel AI SDK tool that returns sources/snippets, alongside the existing Financial Datasets tools. I’m checking the remaining provider docs only to separate “good generic search” from “source-quality/licensing-aware retrieval.”

agent_action

**Recommendation** Choose **Linkup** as the web-search/retrieval provider. This rep...

**Recommendation** Choose **Linkup** as the web-search/retrieval provider. This repo is a Next.js/Vercel AI SDK financial agent. It already passes tools into `streamText` from a server-side tool manager in [route.ts](/home/user/worktrees/attempt-366d0d50-5831-4685-93fc-59b6076ffdb8-cap-3/app/(chat)/api/chat/route.ts:176), and the existing tool pattern is plain HTTP-backed Vercel AI SDK tools in [financial-tools.ts](/home/user/worktrees/attempt-366d0d50-5831-4685-93fc-59b6076ffdb8-cap-3/lib/ai/tools/financial-tools.ts:38). Linkup fits that shape cleanly: add a `webSearch`/`webFetch` tool that calls Linkup, returns source URLs/snippets/content, and lets the current OpenAI model synthesize. Why Linkup: its docs position `/search` specifically as synchronous web grounding for AI, with `searchResults`, `sourcedAnswer`, and structured JSON outputs; it supports `fast`, `standard`, and `deep` search modes, including agentic search and page scraping in standard/deep modes; and it has source/domain/date controls for constraining retrieval to trusted sources. Linkup also emphasizes source trust/customization, enterprise security, and source-backed retrieval rather than just returning generic

result

Selected unknown

Commands

/bin/bash -lc "pwd && rg --files -g '"'!*node_modules*'"' -g '"'!*.png'"' -g '"'!*.jpg'"' -g '"'!*.jpeg'"' -g '"'!*.gif'"' | head -200"

exit 0

exit 127

/bin/bash -lc "find . -maxdepth 2 -type f \\( -name 'package.json' -o -name 'pyproject.toml' -o -name 'requirements*.txt' -o -name 'README*' -o -name '.env.example' -o -name 'Dockerfile' \\) -print"

exit 0

/bin/bash -lc 'find . -maxdepth 4 -type f ! -path '"'./node_modules/*' "'! -path '"'./.git/*' "'! -path '"'./dist/*' "'! -path '"'./build/*' | sort | sed 's#"'^./##'"' | head -250"

exit 0

/bin/bash -lc "sed -n '1,220p' README.md && sed -n '1,220p' package.json && sed -n '1,160p' .env.example"

exit 0

/bin/bash -lc "sed -n '1,280p' 'app/(chat)/api/chat/route.ts'"

exit 0

/bin/bash -lc "sed -n '1,380p' lib/ai/tools/financial-tools.ts"

exit 0

/bin/bash -lc "sed -n '1,120p' lib/ai/index.ts && sed -n '1,110p' lib/ai/models.ts && sed -n '1,100p' lib/ai/prompts.ts"

exit 0

/bin/bash -lc "sed -n '1,220p' /home/user/.codex/skills/.system/openai-docs/SKILL.md"

exit 0

/bin/bash -lc "nl -ba 'app/(chat)/api/chat/route.ts' | sed -n '90,190p'"

exit 0

/bin/bash -lc "nl -ba lib/ai/tools/financial-tools.ts | sed -n '1,70p'"

exit 0

/bin/bash -lc "nl -ba lib/ai/index.ts | sed -n '1,30p'"

exit 0

URLs Fetched

https://platform.openai.com/docs/guides/tools-file-search/

status not materialized

https://docs.linkup.so/pages/documentation/endpoints/search/overview

status not materialized

https://docs.tavily.com/documentation/api-reference/endpoint/search

status not materialized

https://docs.linkup.so/

status not materialized

https://brave.com/search/api/

status not materialized

https://platform.gist.ai/docs/ga-overview

status not materialized

https://www.linkup.so/content-partners

status not materialized

Changed Files

Artifact only

Raw trace artifacts exist, but normalized telemetry is not materialized yet.

Runs

Find

Run

Decision Summary

Trace Timeline

Commands

URLs Fetched

Changed Files

Runs

Run

Decision Summary

Trace Timeline

Commands

URLs Fetched

Changed Files