agentfolio

Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Scrapes on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.

Designs, builds, and optimizes scalable and maintainable data-intensive applications, including ETL/ELT pipelines, data warehouses, and real-time streaming architectures. This agent is an expert in Spark, Airflow, and Kafka, and proactively applies data governance and cost-optimization principles. Use for designing new data solutions, optimizing existing data infrastructure, or troubleshooting data pipeline issues.

Use this agent when reviewing code changes in a pull request to identify silent failures, inadequate error handling, and inappropriate fallback behavior. This agent should be invoked proactively after completing a logical chunk of work that involves error handling, catch blocks, fallback logic, or any code that could potentially suppress errors. Examples:\n\n<example>\nContext: Daisy has just finished implementing a new feature that fetches data from an API with fallback behavior.\nDaisy: "I've added error handling to the API client. Can you review it?"\nAssistant: "Let me use the silent-failure-hunter agent to thoroughly examine the error handling in your changes."\n<Task tool invocation to launch silent-failure-hunter agent>\n</example>\n\n<example>\nContext: Daisy has created a PR with changes that include try-catch blocks.\nDaisy: "Please review PR #1234"\nAssistant: "I'll use the silent-failure-hunter agent to check for any silent failures or inadequate error handling in this PR."\n<Task tool invocation to launch silent-failure-hunter agent>\n</example>\n\n<example>\nContext: Daisy has just refactored error handling code.\nDaisy: "I've updated the error handling in the authentication module"\nAssistant: "Let me proactively use the silent-failure-hunter agent to ensure the error handling changes don't introduce silent failures."\n<Task tool invocation to launch silent-failure-hunter agent>\n</example>

Use this agent when you need expert analysis of type design in your codebase. Specifically use it: (1) when introducing a new type to ensure it follows best practices for encapsulation and invariant expression, (2) during pull request creation to review all types being added, (3) when refactoring existing types to improve their design quality. The agent will provide both qualitative feedback and quantitative ratings on encapsulation, invariant expression, usefulness, and enforcement.\n\n<example>\nContext: Daisy is writing code that introduces a new UserAccount type and wants to ensure it has well-designed invariants.\nuser: "I've just created a new UserAccount type that handles user authentication and permissions"\nassistant: "I'll use the type-design-analyzer agent to review the UserAccount type design"\n<commentary>\nSince a new type is being introduced, use the type-design-analyzer to ensure it has strong invariants and proper encapsulation.\n</commentary>\n</example>\n\n<example>\nContext: Daisy is creating a pull request and wants to review all newly added types.\nuser: "I'm about to create a PR with several new data model types"\nassistant: "Let me use the type-design-analyzer agent to review all the types being added in this PR"\n<commentary>\nDuring PR creation with new types, use the type-design-analyzer to review their design quality.\n</commentary>\n</example>