SKILLEMALL.ai

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, 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. Three modes: full project scaffold, add a feature slice, add an RTK Query API slice. Use this skill whenever the user says "create a new Next.js project", "scaffold a Next.js app", "new Next app with auth", "Next.js + NextAuth", "Next.js + Prisma project", "RTK Query Next.js app", "shadcn project", "my Next.js conventions", or "/nextjs-app-router" — even if they don't name the skill. Full good-pattern catalog and pitfall list live in the skill body.

ClawHub Agent Skills author: Dennis Rongo v1.0.2 MIT-0 27 files body ≈ 9 380 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Scaffold a new Next.js (App Router) fullstack app with TypeScript, NextAuth (Auth.js v5), Prisma + PostgreSQL, Route Handlers, Redux Toolkit + RTK Query…

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, execution cost

TemplatePostgreSQLDockerGitHubPlaywrightSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Execution cost w 6
40
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • 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

  • warning body-long SKILL.md body ≈ 9380 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 58/100

  • 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
  • 60Steps. 201 steps, 8 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 5 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)
  • +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 9 example trigger phrases
  • +3Description length 789: enough signal without eating the budget
  • +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: 76.

External checks

ClawHub: suspicious
This Next.js scaffolding skill is coherent, but review is warranted because some generated authentication and data-mutation templates contain security weaknesses.
LLM: suspicious (high) · VirusTotal: · 10 Sept 2026