SKILLEMALL.ai

BC universal-business-skill-system

通用行业业务技能体系。基于"任务为中心,AI Pipeline驱动"思想,适用于任何行业的结构化业务能力框架。覆盖情报采集、内容生产、活动运营、数据分析、知识管理、合规风控、客户运营、流程协同、资质认证、供应链运营十大业务流。内置12个行业校准模板(消费与零售、平台与数字、专业与知识、制造与工业、强监管、资产运营6大分组),支持轻量校准和完整仿造两种行业适配方式。触发词:业务、运营、技能体系、行业技能、能力单元、Pipeline、业务流程、情报、内容、活动、数据、知识、合规、客户、流程、认证、供应链、行业分析、竞品分析、市场调研、内容营销、活动策划、数据分析、培训、合规审核、客户运营、项目管理、资质认证、供应链管理、行业校准、通用技能。

ClawHub Agent Skills author: 波动几何 v1.0.0 MIT-0 15 files body ≈ 671 tokens Open the sourceclawhub.ai analyzed 2 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
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: 15. 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 671 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 322: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 20 items
  • +4Reference files are cited in the instructions (13 of 13)

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

External checks

ClawHub: clean
This is a broad Markdown-only business workflow skill; it can involve sensitive business or personal data, but I found no hidden code, credential use, exfiltration, or privileged system access.
LLM: benign (high) · VirusTotal: · 29 May 2026