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AC tiered-quantity-discounts-skincare

Designs and implements tiered quantity-break discounts ("buy more, save more") for DTC skincare and beauty stores selling serums, moisturizers, cleansers, and similar replenishment-friendly products. Use whenever the user mentions quantity breaks, tiered pricing, buy 2 save X%, buy 3 get Y% off, volume discount, multi-buy offer, replenishment bundles, serum or moisturizer promotions, stock-up deals, or wants to increase AOV and repeat purchase through graduated discounts. Output structured tier rules, margin-safe discount tables, PDP/cart copy, and measurement plan. Trigger even when the user does not say "quantity break" or "tiered discount" explicitly.

ClawHub Agent Skills author: RIJOY-AI v0.1.1 MIT-0 9 files body ≈ 2 056 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureShopifyWordPressCommercetype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 6. 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 61/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 5 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 7 branches
    • 85Steps. 48 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2056 tokens
    • medium 3 test cases, all positive: not one "should refuse" or "should ask first"

    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

    • +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
    • +5Description quotes 3 example trigger phrases
    • +3Description length 662: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 48 items
    • +4Has examples (0 code blocks)
    • +4Reference files are cited in the instructions (1 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: clean
    This is a benign marketing-planning skill for skincare quantity discounts, with only a minor routing-scope concern around related AOV questions.
    LLM: benign (high) · VirusTotal: · 29 May 2026