BC qa-input-validation
在测试工作流开始前检查用户输入是否包含有效的需求描述和足够的上下文信息。当用户的测试请求过于模糊（只说"帮我测试"却没说测什么）、缺少必要的需求文档或上下文时，应当使用此技能来验证输入完整性。如果输入验证失败，必须返回缺失信息清单要求用户补充。适用于启动任何测试设计流程的第一步。 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
在测试工作流开始前检查用户输入是否包含有效的需求描述和足够的上下文信息。当用户的测试请求过于模糊（只说"帮我测试"却没说测什么）、缺少必要的需求文档或上下文时，应当使用此技能来验证输入完整性。如果输入验证失败，必须返回缺失信息清单要求用户补充。适用于启动任何测试设计流程的第一步。 本技能属于 QA Test…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 0. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "related_skills" - note
frontmatter-keyunknown frontmatter key "input_format" - note
frontmatter-keyunknown frontmatter key "output_format" - note
frontmatter-keyunknown frontmatter key "error_recovery_guidance" - note
frontmatter-keyunknown frontmatter key "categories" - note
frontmatter-keyunknown frontmatter key "depth_requirement_quantification"
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. 8 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 902 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 224: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 8 items
- +4Has examples (9 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.