SKILLEMALL.ai

AC cn-year-end-bonus

Use when asked 年终奖怎么算, 13薪和年终奖有什么区别, 年终奖怎么交税, 单独计税还是并入综合所得, 年终奖被扣了怎么办, 离职了年终奖还发吗, 怎么问 HR 年终奖, or understand a year-end bonus in mainland China. Produces how the person's bonus is likely calculated from their documents, the 13薪 versus discretionary bonus distinction, the tax options with a worked comparison marked to confirm, questions to ask HR or the manager in writing, and the steps if a bonus is withheld after resignation, all marked to confirm against current rules. Not tax or legal advice.

mohitagw15856/pm-claude-skills Agent Skills author: mohitagw15856 MIT 1 file body ≈ 1 331 tokens Open the sourcegithub.com↗ analyzed 3 h ago

Produces how the person's bonus is likely calculated from their documents, the 13薪 versus discretionary bonus distinction, the tax options with a worked…

As a process C 64/100 · Has gaps — weak spots: when it triggers, failures and branches, running it twice

GeneratorFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
64/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: cn-year-end-bonus (mohitagw15856/pm-claude-skills)

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: 1. 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 64/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 37 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1331 tokens

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 499: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 37 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.