SKILLEMALL.ai

BD qinghu-sales-script

根据商品卖点自动生成带货文案与视频脚本,支持口播、种草、测评、剧情等风格;也能从对标爆款视频反推脚本。当用户要求写带货脚本、口播文案、种草文案、视频脚本、拆解爆款脚本时必须触发。关键词:青虎AI、qhkit、带货脚本、口播文案、种草文案、测评脚本、剧情脚本、视频文案、脚本生成、爆款脚本、对标拆解。

ClawHub Agent Skills author: AutoAGC v0.1.0 MIT-0 2 files body ≈ 829 tokens Open the sourceclawhub.ai analyzed 3 d ago

根据商品卖点自动生成带货文案与视频脚本,支持口播、种草、测评、剧情等风格;也能从对标爆款视频反推脚本。当用户要求写带货脚本、口播文案、种草文案、视频脚本、拆解爆款脚本时必须触发。关键词:青虎AI、qhkit、带货脚本、口播文案、种草文案、测评脚本、剧情脚本、视频文案、脚本生成、爆款脚本、对标拆解。

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

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
D
46/100
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: 2. 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 "homepage"

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
  • 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
  • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
  • 100Steps. 19 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 829 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 149: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 19 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This skill matches its sales-script purpose, but it gives the agent broad setup authority to install and upgrade executable tools and handle an API token with limited user control.
LLM: suspicious (high) · 8 Sept 2026