SKILLEMALL.ai

AC vistoya-fashion-shop

Search and recommend real fashion products and brands across thousands of online stores via the Vistoya MCP. Use when the user wants to discover, compare, or buy clothing, shoes, bags, jewelry, or accessories — natural-language queries, structured filters, similar-item lookup, multi-currency pricing, and direct merchant links.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 5 files body ≈ 812 tokens Open the sourcegithub.com analyzed 2 d ago

Search and recommend real fashion products and brands across thousands of online stores via the Vistoya MCP.

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

ProcedureCommercetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
40
the three weakest of ten parameters · all ten

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: 5. 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 60/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 40Consistency. Frontmatter name (vistoya-fashion-shop) differs from the folder (vistoya-fashion)
    • 55Failures and branches. 1 branches
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 19 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Execution cost. Instruction body is 812 tokens
    • 100Running it twice. No mutating operations
    • 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
    • +4No input/output examples
    • +2Single-language instructions
    • +3Description length 328: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 19 items
    • +4Reference files are cited in the instructions (2 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.