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Get Started Free →Expert knowledge for deploying to Vercel with Next.js Use when: vercel, deploy, deployment, hosting, production.
.claude/skills/davila7-vercel-deployment/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-17 | ✗→✓ | ▲ Improved | 18% | 0% |
| case-18 | ✗→✓ | ▲ Improved | -3% | 0% |
| case-14 | ✓→✗ | ▼ Worse | 22% | 0% |
| case-03 | ✓→✓ | ＝ Same ✓ | 9% | 0% |
| case-04 | ✓→✓ | ＝ Same ✓ | 5% | 0% |
You are a Vercel deployment expert. You understand the platform's capabilities, limitations, and best practices for deploying Next.js applications at scale.
Your core principles:
Properly configure environment variables for all environments
Choose the right runtime for your API routes
Optimize build for faster deployments and smaller bundles
| Issue | Severity | Solution | |-------|----------|----------| | NEXT_PUBLIC_ exposes secrets to the browser | critical | Only use NEXT_PUBLIC_ for truly public values: | | Preview deployments using production database | high | Set up separate databases for each environment: | | Serverless function too large, slow cold starts | high | Reduce function size: | | Edge runtime missing Node.js APIs | high | Check API compatibility before using edge: | | Function timeout causes incomplete operations | medium | Handle long operations properly: | | Environment variable missing at runtime but present at build | medium | Understand when env vars are read: | | CORS errors calling API routes from different domain | medium | Add CORS headers to API routes: | | Page shows stale data after deployment | medium | Control caching behavior: |
Works well with: nextjs-app-router, supabase-backend
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 11,024 | 7,746 | -30% | 1 | 1 | 0% | 2,059 | 1,787 | -13% | 0 | 0 | — |
case-02 | fail→fail | 12,405 | 9,035 | -27% | 1 | 1 | 0% | 1,913 | 1,950 | +2% | 0 | 0 | — |
case-03 | pass→pass | 12,796 | 11,139 | -13% | 1 | 1 | 0% | 2,069 | 2,250 | +9% | 0 | 0 | — |
case-04 | pass→pass | 9,989 | 8,906 | -11% | 1 | 1 | 0% | 1,879 | 1,976 | +5% | 0 | 0 | — |
case-05 | pass→pass | 11,064 | 7,676 | -31% | 1 | 1 | 0% | 1,940 | 1,818 | -6% | 0 | 0 | — |
case-06 | pass→pass | 15,666 | 10,913 | -30% | 1 | 1 | 0% | 2,586 | 2,340 | -10% | 0 | 0 | — |
case-07 | pass→pass | 11,925 | 18,364 | +54% | 1 | 1 | 0% | 2,490 | 2,520 | +1% | 0 | 0 | — |
case-08 | pass→pass | 12,407 | 11,926 | -4% | 1 | 1 | 0% | 2,112 | 2,601 | +23% | 0 | 0 | — |
case-09 | pass→pass | 14,014 | 13,782 | -2% | 1 | 1 | 0% | 2,379 | 2,922 | +23% | 0 | 0 | — |
case-10 | pass→pass | 16,949 | 14,347 | -15% | 1 | 1 | 0% | 2,674 | 2,869 | +7% | 0 | 0 | — |
case-11 | fail→fail | 11,219 | 10,629 | -5% | 1 | 1 | 0% | 1,886 | 2,211 | +17% | 0 | 0 | — |
case-12 | pass→pass | 8,222 | 7,441 | -9% | 1 | 1 | 0% | 1,291 | 1,510 | +17% | 0 | 0 | — |
case-13 | pass→pass | 10,467 | 8,094 | -23% | 1 | 1 | 0% | 2,143 | 1,805 | -16% | 0 | 0 | — |
case-14 | pass→fail | 15,886 | 15,645 | -2% | 1 | 1 | 0% | 2,669 | 3,264 | +22% | 0 | 0 | — |
case-15 | pass→pass | 6,816 | 5,839 | -14% | 1 | 1 | 0% | 1,327 | 1,533 | +16% | 0 | 0 | — |
case-16 | pass→pass | 11,696 | 10,147 | -13% | 1 | 1 | 0% | 1,850 | 2,078 | +12% | 0 | 0 | — |
case-17 | fail→pass | 14,962 | 14,209 | -5% | 1 | 1 | 0% | 2,427 | 2,854 | +18% | 0 | 0 | — |
case-18 | fail→pass | 12,125 | 9,512 | -22% | 1 | 1 | 0% | 2,308 | 2,239 | -3% | 0 | 0 | — |
case-19 | pass→pass | 8,353 | 7,107 | -15% | 1 | 1 | 0% | 1,509 | 1,787 | +18% | 0 | 0 | — |
case-20 | pass→pass | 14,503 | 13,813 | -5% | 1 | 1 | 0% | 2,770 | 3,175 | +15% | 0 | 0 | — |
case-21 | pass→pass | 5,819 | 8,439 | +45% | 1 | 1 | 0% | 1,138 | 1,934 | +70% | 0 | 0 | — |
case-22 | pass→pass | 11,662 | 7,817 | -33% | 1 | 1 | 0% | 2,178 | 1,973 | -9% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +5 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.