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The identity layer for AI agents. So your agent stays itself, forever.
1 starsPython
Identa – CLI to calibrate prompts across local LLMs
by srodriguezp·Apr 5, 2026·5 points·0 comments
AI Analysis
●●SolidBig BrainNiche Gem
Cross-model prompt calibration using actual research, not just API chaining.
Strengths
- •Implements PromptBridge paper methodology with MAP-RPE evolutionary loop for real algorithmic depth.
- •Statistical Transfer Gap measurement gives concrete drift metrics between model outputs.
- •Works fully local via Ollama with zero telemetry or cloud dependency.
Weaknesses
- •Prompt optimization space getting crowded with PromptPerfect and similar established tools.
- •Calibration quality hard to verify from README alone without benchmark results.
Category
Target Audience
Developers working with multiple LLM providers or migrating prompts across models
Similar To
PromptPerfect · DSPy · LangChain prompt management
Post Description
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.
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