My trading agent's reflection loop was learning from noise, here's the fix and what's still broken

Posted my paper-trading agent here a few days ago, got good pushback on the self-reflection loop. The core problem: every reflection was written from PnL alone, so a good decision that lost to random noise and an actually bad decision looked identical to the system. That "lesson" then got fed straight into every future prompt with zero filtering. Fixed the first half: reflections now separately judge whether the original entry thesis held up, independent of PnL, and only genuinely flawed theses get carried forward. Still unsolved, someone in the comments pointed out that everything gets dumped into the system prompt every cycle with no retrieval, no tool call, just always-on context. That's the real fix and I haven't touched it yet. If anyone has a clean pattern for agents pulling their own past reasoning on demand instead of force-feeding it, genuinely want to hear it. Link's in the comments if anyone wants to poke at it.