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Consulting Agreement Template - Seeking Feedback

Hacker News

Consulting Agreement Template - Seeking Feedback

https://github.com/sixarm/consulting-agreement I'm doing a yearly update to my free open source consulting agreement template, and seeking suggestions please for any improvements you may see or want. The purpose of this consulting agreement template is to jump-start your own contracts, intended to for for United States startups, consultancies, and independent contracts. I'm specifically seeking experienced advice on how to make the template better, clearer, and more mutually helpful. The template is based on my own interactions with many companies; the template has no AI/ML in it. Thanks!

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Actual performance

5points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, io · Missing: https docs, excited, just released
47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos
26%26% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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