Codebase intelligence for AI. Detects patterns & conventions + remembers decisions across sessions. MCP server for any IDE. Offline CLI.
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 drift'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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Fixed binding alias laundering check
Resolved a bug in the check command where a FROM clause in SQL was incorrectly preventing validation blocks from running. The fix includes comprehensive test coverage for binding alias laundering scenarios and extensive documentation of the validation pipeline architecture.
Merge pull request #132 from dadbodgeoff/remediation/security-convention-s2
Merge pull request #131 from dadbodgeoff/remediation/security-convention-s3
Merge pull request #128 from dadbodgeoff/remediation/security-convention-s1
Merge pull request #126 from dadbodgeoff/remediation/evaluation-receipts
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.