SKILLEMALL.ai

AC buddy-bills

智能收支手帐。记录个人和家庭日常收支、管理固定支出、生成月度汇总报告。 触发场景:用户说"记账"、"花了多少"、"买了xxx花了xxx"、"这个月支出"、"工资发了"、"转账给xxx"、"消费记录"、"月底汇总"、"固定支出"、"收支明细"、"结余多少"、"储蓄率"、"帮我记一笔"、"调出账单"、"查看消费"等与收支记录、财务查询、预算管理相关的请求时触发。

ClawHub Agent Skills author: kiss1952 v1.0.0 MIT-0 6 files body ≈ 384 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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
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: 6. 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. 30 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 384 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

  • +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
  • +5Description quotes 2 example trigger phrases
  • +3Description length 180: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (2 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
This looks like a coherent local finance-recording skill, but it stores and modifies sensitive financial records with broad triggers and not enough upfront consent or retention guidance.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026