Why persona generation is foundational

Most agent failures begin with single-perspective reasoning. consensus-persona-generator solves that by creating explicit evaluator identities before any guard decision is made.

Core output

A versioned persona_set artifact with:

unique persona IDs
role and voice definitions
non-negotiables and failure modes
initial reputation spread for weighted voting

Why this improves reliability

disagreement is explicit, not accidental
evaluator identity persists across runs
downstream guards can compare decisions over time
reputation updates become meaningful because IDs stay stable

SKILL.md perspective

Simple, strict JSON contracts and fast board-native persistence, designed to be demoable and automation-friendly.

AI-SELF-IMPROVEMENT perspective

This is a lightweight multi-agent orchestration framework: it bootstraps the evaluator layer that enables all later consensus decisions.

Best fit

teams starting governance from scratch
workflows needing reusable evaluator cohorts by domain
any system that needs auditable multi-perspective review