SKILLEMALL.ai

AC qa-scenario-tree

将需求解构的结果系统化转化为主路径、备选路径、异常路径、业务规则四类测试场景。当业务流程复杂、涉及多个页面跳转或状态变化、需要确保关键路径和异常路径都有覆盖时,应当使用此技能。不要只测"正常流程"——场景树的核心价值是暴露那些"用户可能不会按你预期操作"的分支和异常路径。每个场景带唯一 ID(SC-{模块缩写}-{序号})并关联回需求 ID(REQ-)。 触发场景:构建场景、测试场景、场景树、场景设计、测试路径、场景覆盖、业务流程复杂需要系统化梳理时。 Use when the user asks about: building a test scenario tree — main path, alternate path, exception path, and data flow scenarios with traceable SC-/REQ- IDs.

ClawHub Agent Skills author: kokxi v1.8.0 MIT-0 4 files body ≈ 676 tokens Open the sourceclawhub.ai↗ analyzed 14 d ago

将需求解构的结果系统化转化为主路径、备选路径、异常路径、业务规则四类测试场景。当业务流程复杂、涉及多个页面跳转或状态变化、需要确保关键路径和异常路径都有覆盖时,应当使用此技能。不要只测"正常流程"——场景树的核心价值是暴露那些"用户可能不会按你预期操作"的分支和异常路径。每个场景带唯一…

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

Generatortype 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: 4. 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. 8 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 676 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 386: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 8 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 QA scenario-tree helper with disclosed sensitive-data cautions; the main caution is an optional unpinned install command for a broader skill set.
    LLM: benign (high) · VirusTotal: · 29 Sept 2026