BC lobsterbrew
Lobster Brew helps your OpenClaw discover coffee roasters, compare coffees, build personalized carts, and hand off a secure Shopify checkout link for you to complete the purchase.
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
GeneratorShopifyCommerceInfrastructuretype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 54/100
- 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
- 40Consistency. Frontmatter name (lobsterbrew) differs from the folder (buy-coffee)
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 65Failures and branches. 3 branches
- 70When it triggers. States when to use, but not when not to
- 100Steps. 55 steps
- 100Execution cost. Instruction body is 1107 tokens
- 100Running it twice. Mutating operations check current state
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- high The skill tells the model to perform an irreversible action with no human approval
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 179: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 55 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.
External checks
ClawHub: clean
This skill is a disclosed coffee-shopping helper that can find merchants and prepare Shopify carts, but it does not contain executable code or attempt payment itself.
LLM: benign (high) · VirusTotal: · 29 May 2026