SKILLEMALL.ai

AC testcase-generator

根据需求文档、PRD、用户故事或接口定义自动生成测试用例。当用户需要根据需求编写测试用例、设计测试场景、生成测试点、创建测试矩阵、或需要测试覆盖分析时使用此技能。也适用于用户提到"生成测试用例"、"写测试点"、"测试场景"、"test case"、"测试覆盖"、"等价类划分"、"边界值分析"、"测试矩阵"、"测试方案"等场景。支持导出为 CSV/Excel 格式。

ClawHub Agent Skills author: ShyLamb-token v1.0.0 MIT-0 2 files body ≈ 1 481 tokens Open the sourceclawhub.ai analyzed 10 h ago

根据需求文档、PRD、用户故事或接口定义自动生成测试用例。当用户需要根据需求编写测试用例、设计测试场景、生成测试点、创建测试矩阵、或需要测试覆盖分析时使用此技能。也适用于用户提到"生成测试用例"、"写测试点"、"测试场景"、"test…

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

GeneratorData and analyticstype 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: 2. 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. 82 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1481 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 2 example trigger phrases
  • +3Description length 183: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 82 items
  • +4Has examples (4 code blocks)

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

External checks

ClawHub: clean
This skill is a coherent test-case generator with optional CSV/Excel export, with only a mild local file-writing caution.
LLM: benign (high) · VirusTotal: · 28 Jul 2026