SKILLEMALL.ai

AC payroll-audit

工资审核 AI 技能。基于审核月份、区域范围、特殊情况,一次性自动生成完整的工资审核报告。 覆盖 10 项核心审核要素(人员范围/入离职/异常检查/考勤/绩效/奖金/社保/个税/人才房/计算逻辑),支持国内和海外员工审核。 三路输出:Markdown 审核报告 + 飞书文档 + HTML 可视化报告(含图表、审核状态追踪、差异对比)。 全流程自动执行,无需人工介入。数据校验采用交叉验证机制。 Use when user asks to 工资审核、薪资审核、月度工资审核、生成工资审核清单、 工资审核报告、本月工资核对、发薪前审核、工资表审核. 不适用于薪酬计算、薪酬对标、调薪方案设计、社保缴纳咨询.

ClawHub Agent Skills author: tuobadaidai v4.0.0 MIT-0 12 files body ≈ 2 063 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

AnalyzerFinanceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
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

    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: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "label"

    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. No external tools needed
    • 100Steps. 67 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2063 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
    • -216 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 302: enough signal without eating the budget
    • +4Structure: 35 headings
    • +3Step-by-step instructions: 67 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This payroll-audit skill appears purpose-built, but it needs review because it handles highly sensitive payroll data with automatic local output, Feishu sharing, and under-scoped write/recovery language.
    LLM: suspicious (high) · 28 May 2026