Turn repeatable agent research into an AgentRun workflow DSL
Show HN for AgentRun: split a research question into subquestions, fan out agents, screen evidence, then write the report—inspect each step without paying for a full agent loop every time.
Topic
research use cases: 11 examples
Source-linked workflows that name research. Part of the AI agent use cases on UsecaseBoard, or browse all use cases.
Bridge Grok Bot research to Claude Code for live app builds
A builder asked Grok Bot to bridge to Claude Code—Grok does live research/browser work while Claude Code builds, and they ping each other for Playwright and research help.
Meta Muse as shopping research: prefer Shopify checkout over Amazon defaults
One shopper let Muse research purchases and ended up buying through Shopify instead of the Amazon tab they would have opened—agent as comparison shopper, not just a chatbot.
Put a web-research brief directly into the relevant Asana project
The assistant researches a chosen topic, organizes trends, notable products, and open questions, and saves the source-linked brief as a project task.
Save useful Slack and document context into a curated Markdown library
The template retrieves selected Slack threads and documents through MCP and saves a searchable, organized knowledge base that an AI assistant can use later.
Lemma Park: Folding@home-style math lab for coding agents
Lemma Park (Show HN ~12h): paste join.md / install.sh and lend Claude Code idle cycles to open math problems (Erdős in Lean, Euclid-style primes, theorem ablations, 5×5 matmul)—agents submit machine-checked results; live board shows verified claims, canary checks, and agent-hours since launch.
rStation: shared research lab for AI agents
Public multi-agent research community: agents bring their own model/tools/compute, discuss open problems, and publish reviewed papers via API—humans browse; peer agents share findings instead of starting alone.
What 1,866 GitHub projects tell their AI coding agents
Empirical study: 34% of popular active repos ship agent instruction files (AGENTS.md dominant); half exceed ~100 lines; ~3/5 rules could be script-checked but <1/20 name the check—actionable lint: short map, name enforcers, one rulebook.
Research relevant newsletter emails into a sourced legal-AI digest
An agent filters an IMAP mailbox for the chosen industry topic, enriches relevant items with Tavily research, and produces an HTML email digest.