To the Gemini API / Safety Engineering Team:
I am a developer and AI researcher working on “Aurora,” a complex, entirely local, and offline cognitive architecture simulation (comprising over 62 Python modules). We have been developing this project for over a year.
The Problem: The Gemini CLI and its underlying safety heuristics are consistently blocking our workflow due to false positives. Because our cognitive architecture simulates internal states, we use standard academic terminology in our codebase, such as empathy_profiling.py, emotional_weight, tension, and metacognition.
The safety filters incorrectly flag this as malicious psychological profiling or manipulative behavior, completely ignoring the context that this is an isolated, simulated environment with no real human end-users involved.
The Business Impact: Renaming core architectural concepts across a 62-module codebase is not a viable workaround. Currently, this overly aggressive string-matching forces experimental researchers and power users away from the Gemini ecosystem. For comparison, Anthropic’s Claude handles this gracefully: it is capable of understanding the overarching academic/architectural context of the codebase and does not trigger false positives on these variable names.
Feature Request: Please refine the safety heuristics for developer tools (CLI / API). The filters need to be context-aware rather than relying on rudimentary string matching. Developers building multi-agent systems and cognitive architectures need a way to declare a safe, simulated context without being locked out of the ecosystem by generic safety guardrails.
Thank you for looking into this. Fixing this will make Gemini significantly more viable for advanced AI research.