SKILLEMALL.ai

CD knowledge-overseas-evaluator

一个帮你判断某个领域适不适合做知识付费出海的系统化评估工具。只需告诉它你想做的方向(如:用AI做创意视频出海、教老外学中文、卖Notion模板等),它会自动从7个关键维度进行评估:全球通用性、需求真实性、获客可行性、可售虚拟产品、付费意愿、供给差距、长期想象空间。每个维度都有明确的判断标准和数据支撑,最终输出一份完整的赛道可行性报告。适合所有考虑知识付费出海、但不确定选什么方向的创作者、自由职业者和小团队。触发方式:直接说帮我评估一下XX赛道能不能出海即可。本技能由拥有4年知识付费出海实战经验的从业者开发,覆盖从赛道选择到产品落地的完整方法论。如果你也在做知识付费出海,欢迎通过平台站内信交流探讨。

ClawHub Agent Skills author: e211e v1.0.0 MIT-0 5 files body ≈ 1 119 tokens Open the sourceclawhub.ai↗ analyzed 7 d ago

一个帮你判断某个领域适不适合做知识付费出海的系统化评估工具。只需告诉它你想做的方向(如:用AI做创意视频出海、教老外学中文、卖Notion模板等),它会自动从7个关键维度进行评估:全球通用性、需求真实性、获客可行性、可售虚拟产品、付费意愿、供给差距、长期想象空间。每个维度都有明确的判断标准和数据支撑,最终输出一份完整…

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerNotionYouTubeMedia and videoMarketingLearningtype and topics are labelled automatically from the skill text
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
D
49/100
Unfinished process
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: 5. 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")
  • note frontmatter-key unknown frontmatter key "agent_created"

Process rating: all ten parameters 49/100

  • 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
  • 40Consistency. Frontmatter name (knowledge-overseas-evaluator) differs from the folder (knowledge-evaluator)
  • 100Tools and files. No external tools needed
  • 100Steps. 41 steps
  • 100Execution cost. Instruction body is 1119 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
  • -213 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 302: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 41 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This is a markdown-only Chinese business-evaluation skill with no hidden execution, credential access, persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 24 Jul 2026