SKILLEMALL.ai

AC blackboard

根据关键词生成深色海报风格插图(竖版 9:16),类似"保姆级教程"封面图风格。 特点:深灰/黑色背景、白色细边框、大字居中中文、高对比度配色(青柠绿+珊瑚红)、 **手写马克笔字体风格**(厚笔触、不规则边缘、真实马克笔质感)、 顶部品牌区、中部标题区、底部标签语,悬挂于白色砖墙。 触发场景:用户说"生成一张海报"、"做个封面图"、"这种风格的图怎么做"、 "生成黑底白字的设计图",或上传参考图要求生成类似风格。

ClawHub Agent Skills author: mingyuan v1.0.2 MIT-0 4 files body ≈ 734 tokens Open the sourceclawhub.ai analyzed 2 d ago

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
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")

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. 11 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 734 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

  • +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 209: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 11 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This appears to be a low-risk image/poster workflow skill with some usability concerns about when it activates and what language it uses.
LLM: benign (medium) · VirusTotal: · 29 May 2026