SKILLEMALL.ai

BD qinghu-shopee-decision

青虎AI Shopee 选品决策:面向重大项目立项,一次串起站点大盘、类目榜单、店铺榜单、商品榜单与热搜词榜四条线,输出「大盘+竞店+爆款+搜词」的全景选品报告与多维度结论。当用户要做 Shopee 选品立项、要一份完整分析报告、要同时看大盘竞店爆款和搜词、要多维度决策依据时必须触发。关键词:青虎AI、Shopee、虾皮、选品决策、立项、全景报告、大盘、竞店、爆款、热搜词、多维分析。

ClawHub Agent Skills author: AutoAGC v0.1.3 MIT-0 2 files body ≈ 1 570 tokens Open the sourceclawhub.ai analyzed 2 d ago

青虎AI Shopee 选品决策:面向重大项目立项,一次串起站点大盘、类目榜单、店铺榜单、商品榜单与热搜词榜四条线,输出「大盘+竞店+爆款+搜词」的全景选品报告与多维度结论。当用户要做 Shopee…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentData and analyticstype 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
D
43/100
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")

Process rating: all ten parameters 43/100

  • 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
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 35 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1570 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

  • +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 193: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 35 items
  • +4Has examples (4 code blocks)

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

External checks

ClawHub: clean
The skill coherently produces paid Shopee market reports through Qinghu APIs, with a disclosed but noteworthy default to save larger data tables locally.
LLM: benign (high) · VirusTotal: · 8 Sept 2026