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: 54. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
warningdescription-no-when description does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 39/100
0Result and completion. Does not say what the result is
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. 6 mutating operations with no state check
40Consistency. Frontmatter name (1688-shopkeeper) differs from the folder (1688-shopkeeper-official)
60Tools and files. Uses tools (python) that frontmatter does not declare
100Steps. 18 steps
100Execution cost. Instruction body is 841 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)
+3Output format is not stated: the model decides each time
+4No input/output examples
-35 of 5 scripts are never mentioned in SKILL.md
+1No license
+2Single-language instructions
+3Description length 241: enough signal without eating the budget
+4Structure: 9 headings
+3Step-by-step instructions: 18 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.
External checks
ClawHub: suspicious
This commerce automation skill is mostly purpose-aligned, but it handles shop credentials and publishing authority in ways users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026