SKILLEMALL.ai

BF geekbi-temu-research-skill

通过极鲸云查询和分析 Temu 商品、图搜同款、店铺、类目、关键词与评论数据,完成跨境电商选品、市场调研、竞品分析、需求趋势、价格带、竞争强度、用户痛点和机会判断。用户提到 Temu 选品、找品、上传图片找同款、拍照搜款、以图搜货、视觉竞品、爆款、新品、蓝海市场、商品表现、店铺研究、竞品店铺、类目规模、品类机会、关键词趋势、搜索需求、市场容量、商品评论、差评原因、使用场景、用户反馈或需要组合多类 Temu 数据形成经营决策时使用。根据用户意图路由一个或多个内部能力,只依据极鲸云真实返回的数据形成结论。

ClawHub Agent Skills author: GeekBI v0.1.0 MIT-0 31 files body ≈ 1 060 tokens Open the sourceclawhub.ai analyzed 3 d ago

通过极鲸云查询和分析 Temu 商品、图搜同款、店铺、类目、关键词与评论数据,完成跨境电商选品、市场调研、竞品分析、需求趋势、价格带、竞争强度、用户痛点和机会判断。用户提到 Temu…

As a process F 35/100 · Will not run — References files that are not bundled: <linkUrl>

Proceduretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: <linkUrl>
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 31. 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")
  • warning missing-ref reference to a missing file: <linkUrl>

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: <linkUrl>
  • 0Tools and files. 1 referenced file(s) missing: <linkUrl>
  • 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
  • 100Steps. 40 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1060 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
  • -31 of 8 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 253: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 40 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (17 of 18)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: clean
This skill is a disclosed Temu market-research integration that queries GeekBI and stores its own GeekBI login state, with no evidence of hidden or unrelated behavior.
LLM: benign (high) · VirusTotal: · 7 Aug 2026