SKILLEMALL.ai

AD vtag-geo-analytics

AI 引擎里的品牌可见度——GA4 看不到的那一段。查你的网站在豆包、DeepSeek、千问、元宝、文心、Kimi 等 AI 引擎里被提到多少、哪些页面被引用,以及 AI 来源的访客、会话与转化;识别得出的分引擎看,识别不出的如实标「来源未知」,不硬凑。数据来自站点自有埋点与引擎应答采样,公开网页上查不到。可回答「我的品牌在 AI 回答里露出多少」「AI 来源带来多少会话和转化」「哪些页面被 AI 引用」。首次使用会引导你在浏览器里完成一次授权。

ClawHub Agent Skills author: Goliver v1.0.3 MIT-0 6 files · 1 script body ≈ 1 219 tokens Open the sourceclawhub.ai analyzed 2 d ago

AI 引擎里的品牌可见度——GA4 看不到的那一段。查你的网站在豆包、DeepSeek、千问、元宝、文心、Kimi 等 AI 引擎里被提到多少、哪些页面被引用,以及 AI…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGoogle AnalyticsData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (vtag-geo-analytics) differs from the folder (geo-analytics)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 25 steps
  • 100Execution cost. Instruction body is 1219 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
  • +2Single-language instructions
  • +3Description length 225: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 25 items
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: clean
This is a coherent read-only analytics skill, but it handles non-public site analytics and a long-lived local access token.
LLM: benign (high) · VirusTotal: · 24 Aug 2026