SKILLEMALL.ai

BC ui-development

Generate production-ready Next.js projects with TypeScript, Tailwind CSS, shadcn/ui, and API integration. Use when the user asks to build, create, develop, or scaffold a Next.js application, web app, full-stack project, or frontend with backend integration. Prioritizes modern stack (Next.js 14+, TypeScript, shadcn/ui, axios, react-query) and best practices. Also triggers on requests to add features, integrate APIs, or extend existing Next.js projects.

modbender/skill-library-mcp Agent Skills author: modbender MIT 3 files · 1 script body ≈ 9 201 tokens Open the sourcegithub.com analyzed 2 d ago

Generate production-ready Next.js projects with TypeScript, Tailwind CSS, shadcn/ui, and API integration. Use when the user asks to build, create, develop, or…

As a process C 53/100 · Has gaps — weak spots: result and completion, consistency, execution cost

GeneratorSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Running it twice w 4
30
Consistency w 8
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 9201 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 53/100

  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 28 mutating operations with no state check
  • 40Consistency. Frontmatter name (ui-development) differs from the folder (frontend-dev)
  • 40Execution cost. Instruction body is 9201 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 179 steps, 2 vague phrases
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 14 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (18 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +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
  • -2localhost URLs: will not work for another user
  • -223 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 455: enough signal without eating the budget
  • +4Structure: 60 headings
  • +3Step-by-step instructions: 179 items
  • +4Has examples (46 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.