Open-source evaluation framework for AI agents

Open-source evaluation framework for AI agents

Indie Hackers

aligned to the OWASP Agentic Security Initiative (ASI)

AI agents are being deployed in production faster than the tooling to evaluate them safely exists. I kept seeing teams ship LangGraph, CrewAI, and AutoGen-based agents with zero adversarial testing.

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Actual performance

1followers
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, agentic · Missing: mac, macos, cursor
97%97% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, lua, io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
31%31% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
19%19% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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