SKILLEMALL.ai

AC qa-test-reporting

输出面向不同受众的测试报告——日报给团队同步进度、周报给项目经理、质量报告给管理层决策。当测试执行完成需要汇总结果、或者上级问"质量怎么样"的时候使用此技能。不同角色关心的数据不同:开发关心Bug明细,经理关心通过率和趋势,老板关心风险和发版决策。报告内容适配受众,关键指标量化呈现,风险区域必须单独成节并醒目标注。 触发场景:测试报告、日报、周报、迭代报告、报告模板、质量汇报、进度汇报、向管理层汇报测试进展时。 Use when the user asks about: writing test reports for different audiences — daily reports for the team, weekly reports for the PM, and quality summaries for management.

ClawHub Agent Skills author: kokxi v1.8.0 MIT-0 4 files body ≈ 556 tokens Open the sourceclawhub.ai↗ analyzed 15 d ago

输出面向不同受众的测试报告——日报给团队同步进度、周报给项目经理、质量报告给管理层决策。当测试执行完成需要汇总结果、或者上级问"质量怎么样"的时候使用此技能。不同角色关心的数据不同:开发关心Bug明细,经理关心通过率和趋势,老板关心风险和发版决策。报告内容适配受众,关键指标量化呈现,风险区域必须单独成节并醒目标注。…

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

GeneratorData and analyticstype 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. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 556 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 377: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (1 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 Chinese QA reporting skill with coherent templates and no artifact-backed evidence of hidden execution, data exfiltration, persistence, or destructive behavior.
    LLM: benign (high) · VirusTotal: · 29 Sept 2026