SKILLEMALL.ai

AC ecommerce-image-diagnosis

电商主图&详情页诊断助手。给它商品主图、详情页截图、搜索结果截图,或者商品链接,自动分析主图点击率潜力与详情页转化率,从视觉清晰度、信息传达、差异化、信任背书、平台合规等10个维度打分,生成结构化 HTML 可视化诊断报告,包含评级、核心发现和 P0/P1/P2 优先改进行动清单。适用于淘宝、拼多多、抖音电商、京东等平台。触发词:主图诊断、详情页诊断、商品图分析、主图优化、详情页分析、电商图片诊断、帮我看看主图、分析详情页、主图好不好、主图转化率、ecommerce image diagnosis。

ClawHub Agent Skills author: bettermen v1.0.0 MIT-0 4 files body ≈ 1 155 tokens Open the sourceclawhub.ai analyzed 35 h ago

电商主图&详情页诊断助手。给它商品主图、详情页截图、搜索结果截图,或者商品链接,自动分析主图点击率潜力与详情页转化率,从视觉清晰度、信息传达、差异化、信任背书、平台合规等10个维度打分,生成结构化 HTML 可视化诊断报告,包含评级、核心发现和 P0/P1/P2…

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

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "agent_created"

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. 49 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1155 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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +3Description length 252: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 49 items
  • +4Has examples (3 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: 74.

External checks

ClawHub: clean
This appears to be a product-listing analysis skill with some broad triggers and automatic link fetching, but no evidence of credential access, persistence, destructive behavior, or deception.
LLM: benign (medium) · VirusTotal: · 18 Jun 2026