SKILLEMALL.ai
GitHub ↗ RU Sign in

AC amazon-listing-image-generation-editing

使用 Nano Banana Pro 规划和生成 Amazon Listing 图片栈，包括主图、功能证据、尺寸、生活方式、使用步骤与包装清单，并保持 ASIN/SKU 事实一致。Use this skill for Amazon Listing 图片生成与编辑、亚马逊主图、Amazon A+、产品图片栈、白底图、infographic、lifestyle image、尺寸图、包装清单和跨境电商素材；通过 AI Hive 生成，提交前复核 Amazon 当前政策。

ClawHub Agent Skills author: Bain Wu v1.0.1 MIT-0 4 files body ≈ 523 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

使用 Nano Banana Pro 规划和生成 Amazon Listing 图片栈，包括主图、功能证据、尺寸、生活方式、使用步骤与包装清单，并保持 ASIN/SKU 事实一致。Use this skill for Amazon Listing 图片生成与编辑、亚马逊主图、Amazon…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorCommerceWriting and documentstype 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
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
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: 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 53/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 5 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 523 tokens
    • 100Running it twice. No mutating operations

    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 234: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 5 items
    • +4Has examples (6 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This skill is a disclosed Amazon listing image-generation helper that uses a fixed external AI service, with expected local image upload and API-key storage behavior.
    LLM: benign (high) · VirusTotal: · 17 Aug 2026