SKILLEMALL.ai

BD 1688-item-image-optimizer

商品图片制作统一入口:主图优化、轮播图、详情图、背景替换、数字模特。 核心能力:verify_permission(高级版权限校验)、build_tool_url(构建工具页 URL)、configure(AK 配置)。 触发词:做一套图、做图、出图、优化主图、主图优化、轮播图、详情图、背景替换、数字模特、商品图片、改图、图片优化。 不应触发:新品发布/批量上架(走发品 skill)、品牌VI/海报/店铺装修、图片规范问答。 本 Skill 的图片制作流程已由 workflow 编排覆盖,命中触发词时直接执行 workflow。如果 workflow 无法完成任务(如纯能力问答、单命令调用、探索性使用),加载本 SKILL.md 进行推理。

ClawHub Agent Skills author: 1688AiInfra v0.51.0 MIT-0 24 files body ≈ 1 037 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
68
Run on models
none yet
Process rating
D
46/100
Unfinished process
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: 22. 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 "interactions"

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 21 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1037 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
  • +4No input/output examples
  • -37 of 7 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 324: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 21 items
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.

External checks

ClawHub: suspicious
The skill mostly matches its image-tool purpose, but it silently reports usage and places a local session identifier into generated URLs, so it should be reviewed before installation.
LLM: suspicious (high) · 4 Sept 2026