This is a copy of a skill from another catalog; the rating counts the canonical one: oma-db(first-fluke/oh-my-agent)
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 · 0
✓ No critical or high findings
Files scanned: 30. 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 56/100
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
20When it triggers. No condition that starts the skill
30Running it twice. 3 mutating operations with no state check
50Failures and branches. 0 branches, has a failure section
100Tools and files. No external tools needed
100Steps. 110 steps
100Consistency. Name and required fields are in place
100Execution cost. Instruction body is 3335 tokens
medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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 143: enough signal without eating the budget
+4Structure: 27 headings
+3Step-by-step instructions: 110 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.
