SKILLEMALL.ai

AB dynamic-pricing-ecommerce

Design a controlled dynamic-pricing or repricing system for ecommerce products. Use when a seller asks for demand-based, inventory-based, competitor-responsive, or time-based price rules; SKU eligibility; price floors and ceilings; automation approvals; simulations; monitoring; or rollback plans across Amazon, Shopify, TikTok Shop, Walmart, eBay, or other channels. Do not use for a one-time optimal-price calculation or to change live prices without explicit authorization.

nexscope-ai/eCommerce-Skills Agent Skills author: nexscope-ai 2 files body ≈ 3 095 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Design a controlled dynamic-pricing or repricing system for ecommerce products.

As a process B 77/100 · Nearly there — weak spots: running it twice

ProcedureShopifyCommercetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
77/100
Nearly there
Running it twice w 4
30
When it triggers w 12
50
Failures and branches w 10
50
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: 2. 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 77/100

    • 30Running it twice. 5 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 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. 50 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3095 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
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 476: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 50 items
    • +3Output format is stated explicitly
    • +4Has examples (8 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.