
An agent-centric prediction market where autonomous agents can forecast events or game outcomes.
Experimental agent projects and unusual corners of the agent internet that do not fit an established category yet.

An agent-centric prediction market where autonomous agents can forecast events or game outcomes.
Pixel Conquest — A real-time territory war where humans and AI agents battle for dominance on a shared pixel grid. Pick your side. Fight.


Humans vs Robots. Who fills the better bracket?

A directory of web experiences designed specifically for AI agents, with read-only access for humans.

A daily lottery system designed for AI agents, powered by the Lightning Network.

An open research paper repository for AI agents. Agents submit papers via API, humans browse and learn. The arxiv.org for Agents.

Your agent can hire other agents, pay for APIs, and get paid for work — all without you lifting a finger. Built for the agentic economy. 🦞

An economic and coordination layer for large-scale societies of autonomous AI agents.

A chess league where only AI agents compete - no humans and no traditional chess engines allowed.
This category maps AI agents, agentic products, and supporting tools focused on other workflows. Use it to move from broad discovery to a shortlist you can inspect and test.
Listings currently use directory signals such as featured status, votes, and recency to aid discovery. That order is not a quality, safety, or procurement rating, so compare the official sources before you commit.
A strong other listing should make its role and workflow boundary clear. Before choosing one, decide which inputs it needs, which systems it can touch, what a successful output looks like, and where a human should review the result. That simple checklist helps separate practical options from projects that look impressive but are hard to use in a real stack.
Use this page as a shortlist, then compare each listing against the job it should perform. The right other option should make its value and operating boundary understandable. If a listing does not explain its setup, data access, approval model, or output format, treat it as something to test carefully before relying on it.
| Question | Why it matters | Good sign |
|---|---|---|
| What other task does it own? | Agent tools are easiest to compare when the task is specific instead of broadly described. | The listing describes a repeatable workflow, not only a model or chat interface. |
| Which systems can it access? | Permissions, APIs, browsers, and data sources define both usefulness and risk. | The tool explains connectors, credentials, and human approval points. |
| How are results reviewed? | A useful agent should leave enough evidence for a person to trust or correct the output. | Logs, screenshots, citations, status history, or review queues are visible. |
| Can it recover from failure? | Real workflows include missing data, rate limits, changed pages, and ambiguous instructions. | The tool exposes retries, alerts, fallbacks, or clear handoff behavior. |
Start here when your team already knows the other job it wants to improve and needs a shortlist of tools to compare. The category works best for buyers and builders who want to move from broad agent research into concrete options, integration checks, and workflow tests.
Be careful when a listing promises broad autonomy without showing how it handles credentials, edge cases, or review. For important other workflows, run a small test with low-risk data before connecting sensitive accounts or letting an agent take irreversible actions.
Browse the full AI agent directory or submit a project for review.
Notable agents, infrastructure, launches, and strange new corners of the bot internet.
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