SKILLEMALL.ai

AC merchant-geo

中小商家免费GEO优化助手。当商家老板需要以下场景时触发: - 发布企业宣传信息到自媒体平台 - 生成符合SEO/GEO优化的文章内容 - 管理企业在抖音、小红书、知乎、百家号、头条号、搜狐号、网易号、快手等平台的品牌内容 - 上传营业执照、门头照片等产品资料自动生成宣传文案 - 客户案例包装和企业口碑内容创作 - 多平台内容一键发布或草稿导出 - 帮我宣传、帮我推广、写篇文章、发到抖音/小红书/知乎 - 上传门头照/产品图/营业执照 触发词示例:"帮我写篇文章宣传我的店"、"上传门头照片"、"生成推广文案"、"发到抖音小红书"

ClawHub Agent Skills author: 寒武纪智能Cambrian Intelligence v1.0.0 MIT-0 10 files body ≈ 1 534 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 51/100 · 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
C
51/100
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: 10. 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 51/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 98 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1534 tokens

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
  • -33 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 267: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 98 items
  • +4Has examples (7 code blocks)
  • +4Reference files are cited in the instructions (4 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
This merchant-promotion skill is mostly purpose-aligned, but it collects sensitive business identity materials and can automate live public posting from logged-in accounts with weak scoping and inconsistent confirmation controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026