BC nextjs-app-router
Scaffold a new Next.js (App Router) fullstack app with TypeScript, NextAuth (Auth.js v5), Prisma + PostgreSQL, Route Handlers, Redux Toolkit + RTK Query, Tailwind + shadcn/ui (Radix), React Hook Form + Zod. Pages are `'use client'` SPA-style — RTK Query talks to in-app `/api/**` Route Handlers; no `fetch()` in server components, no Server Actions, no async `page.tsx`. Use this skill whenever the user asks to "create a new Next.js project", "scaffold a Next.js app", "new Next app with auth", "Next.js + NextAuth", "RTK Query Next.js app", "Next.js + Prisma project", "shadcn project", or mentions "my Next.js conventions". Three modes — (1) full project scaffold, (2) add a feature slice (route + Route Handlers + RTK Query endpoints + Zod schema + form), (3) add an RTK Query API slice for an existing domain. Confirms the database (Postgres + Prisma) and NextAuth providers BEFORE writing any files. Codifies the good patterns (route groups, NextAuth `auth()` in Route Handlers, single base RTK Query + injected endpoints, Prisma singleton, schema-driven forms, per-feature `_components`/`_hooks`) and forbids the pitfalls (`fetch()` / `await db.*` in server components, Server Actions, async `page.tsx`, custom JWT cookies fighting NextAuth, `serializableCheck: false`, `@ts-ignore`, mixed date libraries, `dangerouslySetInnerHTML` without sanitization, multiple `createApi()` instances).
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, execution cost
How to improve
- Shorten the description to 1024 characters.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 27. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1395 chars, limit 1024 - warning
body-longSKILL.md body ≈ 9380 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 62/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Execution cost. Instruction body is 9380 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
- 85Steps. 201 steps, 3 vague phrases
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 15 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low The response is described with custom markup (12 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1395: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- -226 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +5Description quotes 8 example trigger phrases
- +4Structure: 23 headings
- +3Step-by-step instructions: 201 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 48.