SKILLEMALL.ai

AC qa-ai-prompt-strategy

根据不同的测试目标和上下文,选择最佳的提示词模式来驱动AI生成高质量的测试用例。当AI输出的测试用例质量不够好、太泛泛、或者深度不够时,问题往往不在AI而在提示词。此技能提供结构化提示词模板,注入前面步骤产出的分析结果,输出包含角色定义、输出格式规范和约束条件的优化提示词。⚠️ 作为工作流的必过步骤,不得跳过。 触发场景:怎么问AI、AI回答不好、换个方式问、提示词、提问模板、提示词优化、角色扮演、AI输出太浅需要更深时。 Use when the user asks about: choosing or optimizing the prompt that drives test case generation — role definition, output format constraints, and injection of prior analysis results.

ClawHub Agent Skills author: kokxi v1.8.0 MIT-0 3 files body ≈ 663 tokens Open the sourceclawhub.ai↗ analyzed 15 d ago

根据不同的测试目标和上下文,选择最佳的提示词模式来驱动AI生成高质量的测试用例。当AI输出的测试用例质量不够好、太泛泛、或者深度不够时,问题往往不在AI而在提示词。此技能提供结构化提示词模板,注入前面步骤产出的分析结果,输出包含角色定义、输出格式规范和约束条件的优化提示词。⚠️ 作为工作流的必过步骤,不得跳过。…

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
59/100
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

    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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 59/100

    • 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
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 663 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 397: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 9 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a read-only prompt-template skill for QA test-case generation, with some broad activation wording and an optional unpinned install suggestion users should treat carefully.
    LLM: benign (high) · VirusTotal: · 29 Sept 2026