AB spraay-shopify-selfhost
Deploy and self-host the open-source Spraay Shopify app (batch USDC payouts on Base) for a merchant's store. Use this skill whenever a user wants to install, deploy, set up, self-host, or troubleshoot the Spraay Shopify app (github.com/plagtech/spraay-shopify) - including creating the custom app in the Shopify Dev Dashboard, deploying to Railway, configuring environment variables, setting up the Supabase/Postgres database, fixing 502 errors or OAuth redirect issues, or connecting a custom domain. Also use when a Shopify merchant asks how to add crypto payouts, USDC payments, or affiliate crypto payments to their store admin.
Deploy and self-host the open-source Spraay Shopify app (batch USDC payouts on Base) for a merchant's store.
As a process B 69/100 · Nearly there — weak spots: result and completion, running it twice
How to improve
- 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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:16High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- Base (chain 8453), USDC `0x83…913`
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:17High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- Batch contract `0x16…eEC` (verified; never substitute another address)
quoted
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 69/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 11 mutating operations with no state check
- 60Tools and files. Uses tools (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
- 100Steps. 32 steps
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1852 tokens
- 100Progress reporting. Reports progress
- 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
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 632: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.