AB knowledge-gap-map
Map what you don't know about a subject — including the gaps you can't see — so your learning targets the holes instead of re-covering what you already know. Use when asked what don't I know about X, find my knowledge gaps, what should I learn next in, or map my understanding of. Produces a picture of the subject's territory, what you already know vs the gaps, the dangerous unknown-unknowns (things you don't know you're missing), which gaps matter most for your goal, and a prioritized learn-next list — so effort goes where it counts.
Map what you don't know about a subject — including the gaps you can't see — so your learning targets the holes instead of re-covering what you already know.
As a process B 70/100 · Nearly there — weak spots: when it triggers, failures and branches, progress reporting
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 · 0
✓ No critical or high findings
Files scanned: 1. 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 70/100
- 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
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 29 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 834 tokens
- 100Running it twice. No mutating operations
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)
- +1No license
- +2Single-language instructions
- +3Description length 539: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 29 items
- +3Output format is stated explicitly
- +4Has examples (0 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.