SKILLEMALL.ai

AC gtyt-reconcile

共同赢(GTYT)供应商账单与到货单的三阶段对账流程。用于按月核对「共同赢X月账单-上海-共同赢.xls」与「到货单明细表」在每店每产品上的「单价」「数量」「金额」是否一致,输出两份 Excel:(1) 两表金额差异对比 .xls(全量店名对比 + 25 店差异清单),(2) 共同赢X月账单-已标差异 .xls(在原账单上用黄色背景标出每个差异单元格)。触发关键词:「对账」「核对」「共同赢」「到货单差异」「标差异」「账单 vs 到货」。

ClawHub Agent Skills author: CharlesOYoung v1.0.0 MIT-0 7 files body ≈ 561 tokens Open the sourceclawhub.ai analyzed 3 d ago

共同赢(GTYT)供应商账单与到货单的三阶段对账流程。用于按月核对「共同赢X月账单-上海-共同赢.xls」与「到货单明细表」在每店每产品上的「单价」「数量」「金额」是否一致,输出两份 Excel:(1) 两表金额差异对比 .xls(全量店名对比 + 25 店差异清单),(2) 共同赢X月账单-已标差异…

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

ReferenceData and analyticsFinanceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
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. 27 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 561 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 220: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 27 items
  • +4Has examples (1 code blocks)
  • +3All 5 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: suspicious
This skill appears to do the advertised reconciliation work, but it handles sensitive business spreadsheets with under-scoped local staging and outbound delivery.
LLM: suspicious (high) · 7 Sept 2026