vercel-optimize

Audits Vercel projects using observability metrics to produce ranked cost and performance recommendations.

Updated Aug 11, 2026
One-click install
npx skills add https://github.com/Debindenny/travelplanner-community- --skill vercel-optimize-debindenny
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: vercel-optimize
Source: https://github.com/Debindenny/travelplanner-community-/tree/main/travel-planner/agent-skills/skills/vercel-optimize
Command: npx skills add https://github.com/Debindenny/travelplanner-community- --skill vercel-optimize-debindenny

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve? Vercel bills and slow routes are hard to diagnose because cost and latency signals live in observability data while fixes live in source code. This Skill connects the two by collecting Vercel metrics first, then investigating only the routes and files those metrics implicate, so every recommendation is backed by observed evidence rather than guesswork. ## Core Features & Use Cases - Metric-driven audits: Collects route-level function invocations, duration, cache hit rates, Core Web Vitals, ISR activity, and billing usage via the Vercel CLI before reading any source files. - Deterministic gating: Pure-JavaScript threshold gates decide which candidates deserve investigation, with a default budget of 6 code-scope candidates and an optional user-approved expansion. - Verified recommendations: Every recommendation is checked against real files, an allow-listed citation library, and the detected framework version before appearing in the final Markdown report. - Use Case: A team notices their Vercel bill doubled. They run the audit from the linked project directory, and the Skill identifies an uncached high-traffic route, an over-aggressive ISR revalidate interval, and a broad middleware matcher, each with before/after code and documentation citations. ## Quick Start From a linked Vercel project directory, ask your coding agent to optimize this Vercel project and reduce its cost and slow routes.

Frequently Asked Questions about vercel-optimize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reduce my Vercel bill with this skill?▼

Run the audit from your linked Vercel project directory and ask your agent to optimize the project. It collects usage and metrics first, gates candidates with deterministic thresholds, and returns ranked recommendations tied to observed billing dimensions like function duration, edge requests, and ISR.

How does the Vercel optimization audit work?▼

The audit collects Vercel metrics, usage, and project config via the CLI, scans the codebase, then merges signals and gates candidates with deterministic JavaScript thresholds. Only metric-backed candidates are investigated, and every recommendation is verified against real files and allow-listed documentation citations before rendering.

Which frameworks are supported for Vercel route optimization?▼

Next.js App Router and Pages Router have the strongest support, SvelteKit and Nuxt are supported with route mapping, and Astro has limited support. Hono, Remix, and unknown frameworks are blocked by default unless you accept a limited platform and scanner-only audit.

What are the requirements to run a Vercel cost audit?▼

You need Node.js 20+, Vercel CLI v53 or later with metrics, usage, contract, and api commands, an authenticated CLI session, and a linked project directory via vercel link. Observability Plus is required for route-level metric-backed recommendations.

Why does the audit pause when route metrics are unavailable?▼

The skill refuses to silently fall back to code-only mode because scanner findings alone cannot rank hot routes or prove cost impact. It presents a choice: enable Observability Plus and rerun the metric-backed audit, or accept a limited code-only run.

Does the skill estimate exact dollar savings for recommendations?▼

No. Cost impact is framed using magnitude phrases rather than precise dollar projections, because exact savings cannot be verified from the available signals. Recommendations always cite observed metric evidence instead of invented savings figures.