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AC sveltekit-webapp

Scaffold and configure a production-ready SvelteKit PWA with opinionated defaults. Use when: creating a new web application, setting up a SvelteKit project, building a PWA, or when a user asks to "build me an app/site/webapp". Handles full setup including TypeScript, Tailwind, Skeleton + Bits UI components, testing, linting, and Vercel deployment. Generates a PRD with user stories for review, then upon user approval, builds through development, staging, and production with user approval at each stage.

modbender/skill-library-mcp Agent Skills author: modbender MIT 7 files body ≈ 5 124 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Scaffold and configure a production-ready SvelteKit PWA with opinionated defaults.

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, running it twice

TemplateGitHubPlaywrightSoftware developmentInfrastructureData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
58/100
Has gaps
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5124 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "requires_tools"
  • note frontmatter-key unknown frontmatter key "safety_notes"

Process rating: all ten parameters 58/100

  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 34 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5124 tokens
  • 85Steps. 100 steps, 2 vague phrases
  • 100Consistency. Name and required fields are in place
  • low 13 top-level sections: this looks like several domains in one skill

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 506: enough signal without eating the budget
  • +4Structure: 50 headings
  • +3Step-by-step instructions: 100 items
  • +4Has examples (18 code blocks)
  • +4Reference files are cited in the instructions (2 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.