AD food-recall-radar
Use when you want to check whether food you actually bought is affected by an active recall, after hearing news of an outbreak or a brand recall, when organizing the pantry, after a grocery run, or on a schedule (weekly recall audit) — builds a personal pantry inventory of brands/products/UPCs, queries openFDA's live food-enforcement recall database, fuzzy-matches your items against ongoing Class I/II/III recalls with lot-code pattern extraction, and outputs a risk-ranked action list (check / discard / return-for-refund).
Use when you want to check whether food you actually bought is affected by an active recall, after hearing news of an outbreak or a brand recall, when…
As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
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: 7. 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 47/100
- 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
- 30Running it twice. 3 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 21 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1929 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
- +3Output format is not stated: the model decides each time
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 527: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 21 items
- +4Has examples (6 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.