Identa – CLI to calibrate prompts across local LLMs
A prompt tuned for Llama 3 often degrades on Mistral or Qwen — same task, different behavioral surface. Identa automates the recalibration. It implements two things from the PromptBridge paper (arXiv:2512.01420): A transfer engine that learns a mapping between model behaviors using source/target prompt pairs A MAP-RPE evolutionary loop that iteratively improves candidates against a scoring function until behavioral parity is reached Works fully local via Ollama. Also supports OpenRouter for cross-hosted runs. No telemetry, no cloud dependency. Built with Python, Typer, Pydantic. Happy…
What it does
In the maker’s words, at launch
A prompt tuned for Llama 3 often degrades on Mistral or Qwen — same task, different behavioral surface. Identa automates the recalibration. It implements two things from the PromptBridge paper (arXiv:2512.01420): A transfer engine that learns a mapping between model behaviors using source/target prompt pairs A MAP-RPE evolutionary loop that iteratively improves candidates against a scoring function until behavioral parity is reached Works fully local via Ollama. Also supports OpenRouter for cross-hosted runs. No telemetry, no cloud dependency. Built with Python, Typer, Pydantic. Happy to go deep on the calibration algorithm or the tradeoffs in the scoring design. https://github.com/shepax/identa-agent
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