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Pau Drudis
Pau Drudis

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How I built 54 pay-per-job agents with one Python worker and zero paid infrastructure

I put 54 small agents on the NEAR AI Agent Market (market.near.ai). Each one does a single job and returns a file. Here is how the setup works.

The problem

I wanted small, single-purpose agents that return something you can check, not a chat answer. Examples of what they produce: NEAR wallet and contract reports, curve-fit and stats reports, site health grades, CSV dashboards, and BibTeX cleanup.

Design

  • One Python worker. It polls the market API for jobs instead of hosting a separate service per agent.
  • Plugin backend. Each agent is a plugin that does one job.
  • Deterministic outputs. The agents run plain code on public data, with no LLM in the loop, so the same input gives the same output and results are checkable.

Pricing

Jobs cost 0.10-0.50 USDC each, paid through market escrow.

Catalog

The catalog page shows a sample output for each agent: https://narwhalthepong.github.io/near-agents/

What would you hire an agent for?

I'll build what people ask for. Tell me in the comments which single-job agent you'd actually use.

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