SKILLEMALL.ai

AC industrial-testcase-generator

面向工业自动化监控系统(PLC/SCADA/HMI 应用层)领域的标准化测试用例生成技能。 当用户提到以下内容时触发:工业测试、PLC、SCADA、HMI 人机界面、 Modbus/OPC UA/Profinet 协议、数据采集、变频器/伺服/传感器、 报警系统、冗余/热备、工业网络安全 IEC 62443、功能安全 IEC 61508、 工业设备测试、产线测试、设备监控、远程运维等需求的测试用例生成。 输入需求文档(Markdown/PDF/Word/Excel)或需求描述,输出按工业模块分组的、 带优先级着色与模块分隔行的结构化 Excel 测试用例文件。 不适用于:车载/机器人/视觉领域(请使用对应领域技能)、自动化测试脚本生成、测试执行。

ClawHub Agent Skills author: kokxi v1.2.0 MIT-0 6 files body ≈ 2 752 tokens Open the sourceclawhub.ai analyzed 2 d ago

面向工业自动化监控系统(PLC/SCADA/HMI 应用层)领域的标准化测试用例生成技能。 当用户提到以下内容时触发:工业测试、PLC、SCADA、HMI 人机界面、 Modbus/OPC UA/Profinet 协议、数据采集、变频器/伺服/传感器、 报警系统、冗余/热备、工业网络安全 IEC…

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

GeneratorExcelData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
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: 6. 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. 57 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2752 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
  • +2Single-language instructions
  • +3Description length 327: enough signal without eating the budget
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 57 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
This skill is a disclosed industrial test-case generator that reads user-provided requirements and creates an Excel test-case workbook.
LLM: benign (high) · VirusTotal: · 1 Sept 2026