SKILLEMALL.ai

BD qinghu-douyin-bluesea-collector

青虎AI 抖音蓝海爆品采集:结合抖音热搜榜与关键词下的视频数据,从小众高需求的细分场景切入找蓝海爆品,避开红海大词竞争,并接 1688 关键词搜索与以图搜款完成货源采集。当用户要在抖音找蓝海品、避开大词竞争、从细分场景选品、看抖音热搜、按关键词看视频热度、找同款货源时必须触发。关键词:青虎AI、抖音、蓝海、爆品、细分场景、热搜榜、关键词、选品、货源、1688。

ClawHub Agent Skills author: AutoAGC v0.1.3 MIT-0 2 files body ≈ 1 499 tokens Open the sourceclawhub.ai analyzed 3 d ago

青虎AI 抖音蓝海爆品采集:结合抖音热搜榜与关键词下的视频数据,从小众高需求的细分场景切入找蓝海爆品,避开红海大词竞争,并接 1688…

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. 33 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1499 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 181: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (4 code blocks)

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

External checks

ClawHub: clean
This skill is a disclosed Douyin product-research workflow that uses Qinghu APIs and may create local exports, with no evidence of hidden execution or malicious behavior.
LLM: benign (high) · VirusTotal: · 8 Sept 2026