SKILLEMALL.ai

BC neway-commerce-os

Generate, scaffold, build, and prepare deployment for a reusable react + vite + hono commerce operating system focused on digital products, storefronts, subscriptions, ai-assisted sales, admin dashboards, and international stripe-style payments. use when the user wants a complete website skeleton from a short prompt, especially for ecommerce launches, creator stores, productized services, multi-product studios, or newaystudio-style product matrices with edgeone pages deployment and full-stack edge functions.

ClawHub Agent Skills author: Neway Lau v1.0.1 MIT-0 43 files body ≈ 6 562 tokens Open the sourceclawhub.ai analyzed 31 h ago

Generate, scaffold, build, and prepare deployment for a reusable react + vite + hono commerce operating system focused on digital products, storefronts…

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorStripeSoftware developmentDesignInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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: 42. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6562 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 55/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 10 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
  • 60Steps. 149 steps, 7 vague phrases
  • 70Execution cost. Instruction body is 6562 tokens
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (9 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
  • -2localhost URLs: will not work for another user
  • -217 emoji in the instructions: noise for the model
  • -44 reference files, but SKILL.md never points to them: the model will not open them
  • -32 of 2 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 513: enough signal without eating the budget
  • +4Structure: 39 headings
  • +3Step-by-step instructions: 149 items
  • +4Has examples (13 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: suspicious
The skill is a coherent commerce-site scaffold, but it needs Review because it can delete an existing output project without confirmation and its payment/security scaffolding can be mistaken for production-ready checkout.
LLM: suspicious (high) · 2 Jun 2026