SKILLEMALL.ai

BC customer-service-performance

客服坐席绩效核算技能。读取用户提供的坐席工作量数据表与绩效规则表(Excel/CSV 均可),按可配置的多维度权重与阶梯规则逐人核算得分,输出含逐项计算过程的绩效明细表、团队分布对比与待人工复核清单。适用场景:客服绩效核算、坐席绩效、月度绩效统计、绩效评分、按规则算绩效,以及用户提供坐席数据与考核规则并希望自动核算得分的任务。核算结果供人工复核参考,不构成最终考核依据。本技能面向中文绩效场景设计。反馈与定制联系:zenobiazizi.skills@foxmail.com

ClawHub Agent Skills author: zenobiazizi v1.1.0 MIT-0 7 files body ≈ 535 tokens Open the sourceclawhub.ai analyzed 3 d ago

客服坐席绩效核算技能。读取用户提供的坐席工作量数据表与绩效规则表(Excel/CSV…

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

ProcedureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

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. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 535 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
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +3Description length 238: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 20 items
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: clean
This skill locally calculates customer-service performance reports from user-provided data and includes appropriate review warnings for sensitive employee scoring.
LLM: benign (high) · VirusTotal: · 6 Aug 2026