SKILLEMALL.ai

BC bookkeeping-agency-skill-system

代理记账行业十大功能集群技能体系。基于"任务为中心,AI Pipeline驱动"思想,覆盖市场情报、内容获客、增长引擎、经营分析、财税知识、合规风控、客户全周期、服务流程、资质准入、工具与供应链十大业务流。专注代理记账、工商注册、税务申报、汇算清缴、税务筹划、财税咨询等代理记账机构全业务场景。触发词:代理记账、代账、财税、报税、纳税申报、汇算清缴、工商注册、税务筹划、金税四期、全电发票、数电票、税负率、凭证、账簿、财务报表、会计准则、小规模纳税人、一般纳税人、查账征收、核定征收、记账公司、财税公司、bookkeeping、tax filing、accounting agency。

ClawHub Agent Skills author: 波动几何 v1.0.0 MIT-0 14 files body ≈ 810 tokens Open the sourceclawhub.ai analyzed 4 d ago

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

ProcedureInfrastructureFinancetype 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: 14. 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 810 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 293: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 30 items
  • +4Reference files are cited in the instructions (12 of 12)

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

External checks

ClawHub: suspicious
This accounting-agency skill is not clearly malicious, but it describes broad automation over sensitive financial, customer, employee, and communications data without enough privacy, consent, or human-review safeguards.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026