AC kohls-research
Researches Kohl's catalog by browsing its category taxonomy (products, prices, ratings, and facets), pulls product reviews by web_id, finds nearby Kohl's stores, and returns search-box typeahead suggestions — all via the Crawlora API as clean JSON. Use when the user asks to browse a Kohl's category, discover Kohl's product ideas for a query, pull reviews for a specific Kohl's item, or find nearby Kohl's stores — instead of scraping Kohls.com.
Researches Kohl's catalog by browsing its category taxonomy (products, prices, ratings, and facets), pulls product reviews by webid, finds nearby Kohl's…
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
The same skill appears in 1 more place: ClawHub
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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Exfiltration
net-credential-usescripts/crawlora.sh:16Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host; quoted — discussed, not commanded): "${CRAWLORA_API_KEY:?Set CRAWLORA_API_KEY first — get a free key at https://crawlora.net?utm_source=…&utm_medium=…&utm_campaign=…"vendor-hostquoted -
low Exfiltration
net-credential-usescripts/crawlora.sh:77Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)printf 'header = "x-api-key: %s"\n' "$CRAWLORA_API_KEY" >"$curl_config"
quoted
Files scanned: 4. 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 62/100
- 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
- 30Running it twice. 2 mutating operations with no state check
- 100Tools and files. No external tools needed
- 100Steps. 22 steps
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1337 tokens
- 100Progress reporting. Reports progress
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
- +1No license
- +2Single-language instructions
- +3Description length 446: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.