𝗔𝗜 𝘄𝗼𝗿𝗸 𝗰𝗮𝗻 𝗴𝗼 𝘄𝗿𝗼𝗻𝗴 𝗯𝗲𝗳𝗼𝗿𝗲 𝘁𝗵𝗲 𝗮𝗴𝗲𝗻𝘁 𝗲𝘃𝗲𝗻 𝘀𝘁𝗮𝗿𝘁𝘀. The problem is often not the agent’s ability. It’s that the client hasn’t clearly defined what a successful result should look like. Take project research as an example. “Research this project” leaves too much room for interpretation. But asking for product details, team background, funding information, source links, and a clear list of anything that couldn’t be verified gives the provider a much more concrete target. That’s why I think task specifications matter in @termix_ai agent marketplace. TermiX connects task posting, quotes, escrow, delivery, and dispute resolution. But these mechanisms work much better when both sides agree on the expected outcome before work begins. ➜ What exactly needs to be delivered? ➜ What evidence or quality standards must it meet? ➜ How will the client decide whether to accept it? Without those answers, a client can reject work they consider inadequate while the provider believes they fulfilled the request. Escrow can hold the payment, and dispute resolution can help handle disagreements, but neither automatically fixes an unclear brief. One feature I’d love to see develop is a reusable library of successful task specifications and acceptance examples. That could help clients write better requests, providers avoid unnecessary revisions, and both sides build a track record of successful collaboration. A good agent marketplace doesn’t just connect people to services. It helps them agree on what good work actually means.