SKILLEMALL.ai

AC shopify-expert

Builds and debugs Shopify themes (.liquid files, theme.json, sections), develops custom Shopify apps (shopify.app.toml, OAuth, webhooks), and implements Storefront API integrations for headless storefronts. Use when building or customizing Shopify themes, creating Hydrogen or custom React storefronts, developing Shopify apps, implementing checkout UI extensions or Shopify Functions, optimizing performance, or integrating third-party services. Invoke for Liquid templating, Storefront API, app development, checkout customization, Shopify Plus features, App Bridge, Polaris, or Shopify CLI workflows.

Jeffallan/claude-skills Agent Skills author: Jeffallan MIT 6 files body ≈ 1 548 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Builds and debugs Shopify themes (.liquid files, theme.json, sections), develops custom Shopify apps (shopify.app.toml, OAuth, webhooks), and implements…

As a process C 52/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

GeneratorShopifySoftware developmentCommercetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
99
Quality 40%
92
Run on models
none yet
Process rating
C
52/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Exfiltration exfil-webhook-url references/checkout-customization.md:826
      Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
      npm run shopify app dev --tunnel-url="https://your-ngrok-url.ngrok.io"
      placeholder

    Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 152, 155): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 52/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 9 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 100Steps. 29 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1548 tokens

    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)
    • +2Single-language instructions
    • +3Description length 603: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 29 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.