scoring-checks

# Adding a Scoring Check Add a new deterministic check that evaluates a single aspect of AI agent config quality. All checks must be filesystem-based with no network calls or LLM inference. ## Critical - **Check must be deterministic**: Same filesystem state → same result every time. No randomness, no external APIs. - **Point values come from constants.ts**: Every `earnedPoints` and `maxPoints` must reference `POINTS_*` from `src/scoring/constants.ts`. Do NOT hardcode numbers. - **Always return `Check[]` array**: Export a function `check<Category>(dir: string): Check[]` where category is one of: `existence`, `quality`, `grounding`, `accuracy`, `freshness`, `bonus`. - **Every check must have**: `id` (kebab-case, unique), `name`, `category`, `maxPoints`, `earnedPoints`, `passed`, `detail`, and optional `suggestion`/`fix`. - **Fix object fields**: `action` (string describing what to do), `data` (context for the fix), `instruction` (user-facing guidance). - **Register in src/scoring/index.ts**: Add the import and spread the result into the `allChecks` array in `computeLocalScore()`. - **Target filtering**: If the check is platform-specific (Claude-only, Cursor-only, etc.), add its ID to the appropriate `*_ONLY_CHECKS` set in `constants.ts`. ## Instructions ### Step 1: Define point constants in src/scoring/constants.ts Verify before proceeding: Is your check measurable with a numeric point value? Add constants below the appropriate category section (existence, quality, grou...