SKILLEMALL.ai

BC qa-risk-intuition

识别那些"看起来很简单但实际风险很高"的测试区域,帮你在有限的测试资源下做优先级判断。当测试时间不够、不知道应该重点测哪些功能、或者直觉告诉你某个功能可能有问题但说不上来为什么时,应当使用此技能。典型的危险信号包括:频繁变更的模块、第三方依赖、资金/安全相关功能、历史Bug多发区域。每一个识别出的风险点都需要标注概率和影响等级,并附上缓解建议。 本技能属于 QA Test Skills 技能集(49 个技能之一),完整工作流体验需安装全套:npx skills add Kokxi/qa-test-skills

ClawHub Agent Skills author: kokxi v1.7.6 MIT-0 3 files body ≈ 712 tokens Open the sourceclawhub.ai analyzed 2 d ago

识别那些"看起来很简单但实际风险很高"的测试区域,帮你在有限的测试资源下做优先级判断。当测试时间不够、不知道应该重点测哪些功能、或者直觉告诉你某个功能可能有问题但说不上来为什么时,应当使用此技能。典型的危险信号包括:频繁变更的模块、第三方依赖、资金/安全相关功能、历史Bug多发区域。每一个识别出的风险点都需要标注概率…

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

Proceduretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
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: 3. 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 "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "related_skills"
  • note frontmatter-key unknown frontmatter key "references"
  • note frontmatter-key unknown frontmatter key "input_format"
  • note frontmatter-key unknown frontmatter key "output_format"
  • note frontmatter-key unknown frontmatter key "depth_requirement_quantification"
  • note frontmatter-key unknown frontmatter key "categories"
  • note frontmatter-key unknown frontmatter key "error_recovery_guidance"

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. Tools declared in frontmatter
  • 100Steps. 16 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 712 tokens
  • 100Running it twice. No mutating operations
  • low 10 top-level sections: this looks like several domains in one skill

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 257: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 16 items
  • +4Has examples (8 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This skill is a coherent QA risk-assessment guide with read-only tool access and no hidden persistence or mutation behavior.
LLM: benign (high) · VirusTotal: · 1 Sept 2026