v0.2.0-alpha.5 — Repo Native

What's new

Repo-aware fixes (Taste Atlas). bluei now considers each repo's preferred conventions when generating fixes. A seed library of framework-specific conventions (Django, pytest, React) is injected into LLM fix prompts — so a Django repo gets fix suggestions that respect Django idioms, not generic Python advice. This is the first step toward bluei understanding how each repo prefers its code.

Campaigns as evidence instruments (Campaign Lab). Campaigns can now declare a learning objective — a target asset to gather evidence for. A campaign targeting an emergent rule will run shadow validation to advance its lifecycle. One targeting a pattern family will collect dry-replay evidence to feed future promotion decisions. Campaigns gather evidence only; they never make governance decisions.

Graduated plugin detectors. Emergent rules that prove themselves through shadow validation can now be promoted into standalone plugin detectors. A build-time generator produces a complete, self-contained plugin pack from any graduated rule. The first worked example ships: an eslint no-console detector that runs without wrapping an external linter.

Structural code matching. Emergent rules can now match code by its AST shape, not just by text or regex. A rule learned from one snippet will catch structurally similar code even when variable names differ. Python-only in this release; TypeScript structural matching is deferred.

Stats

• 6,463 tests (+62 from alpha.4), 0 regressions
• Zero new architecture decisions (integration release — all four features wire existing infrastructure)
• All mechanisms proven by synthetic tests only (no live repo runs until 0.2.0 stable)