GCP Config Connector, a Kubernetes add-on for managing GCP resources
A deterministic 0–100 hygiene score — README, license, CI, tests, docs, and freshness.
Who ships this repo — author concentration and the bus factor across the last 300 mainline commits.
How welcoming this repo is to contributors — issue throughput, close time, responsiveness, and good-first-issue count.
What this project is built on — dependency count by ecosystem, the license mix, and anything worth a legal look before you adopt it.
Whether this project's CI can be trusted — pass rate, run times, flaky runs, and which workflow is the weak link.
Grounded in k8s-config-connector's README, structure, and recent commits — answers won't invent code they haven't seen.
A Monday email with what shipped, in plain English — no account needed.
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ai:chore: Implement direct types for: OracleDatabaseAutonomousDatabase (#13414)
Greenfield: Implement direct controller, E2E fixtures, and fuzzer for DataplexMetadataFeed (#13479)
Greenfield: Implement MockGCP and Alignment for DiscoveryEngineSitemap (#13766)
Greenfield: Implement MockGCP and Alignment for DataformFolder (#13510)
direct/compute: align ComputeRouterNAT create defaults and delete behavior with legacy controller (#13787)
PubSubTopic: use canonical kmsv1beta1.KMSCryptoKeyRef for spec.kmsKeyRef (#13745)
Greenfield: Implement MockGCP and Alignment for NetworkServicesLBTrafficExtension (#13779)
Greenfield: Implement MockGCP and Alignment for MigrationCenterPreferenceSet (#13763)
Greenfield: Implement direct KRM types, identity, and generate.sh for NetworkServicesServiceLBPolicy (#13338)
A floor, not a guess: counts only commits whose author, co-author trailer, or message explicitly credits an AI tool (Claude, Copilot, Cursor, aider, Codex…). Based on 30 mainline commits. Unattributed AI code isn't counted here — the full audit estimates that separately.