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AD cn-ecommerce-ops

国内电商全链路运营专家技能，覆盖淘宝、天猫、京东、拼多多、抖音电商、小红书、视频号、Temu八大平台。提供选品评分、定价与利润测算（含达人佣金）、广告投放ROI测算、店铺转化漏斗诊断、广告法违禁词合规检查、商品标题生成、备货与资金占用测算七个可计算工具，以及一个实时数据桥接器(live.py)——先用 WebSearch/WebFetch 拉取当前真实佣金率、类目退货率、1688进货价、关键词搜索量，再一键灌入各计算器，实现"实时可用"的决策。当用户涉及国内电商选品、定价、算利润、算ROI、投直通车或千川、做店铺诊断、写商品标题、算备货量、优化标题主图详情页、写商品文案、直播运营、检查文案是否违反广告法、Temu全托管半托管报价与合规、平台规则与流量玩法，或需要查最新费率/获取实时行情来辅助决策时，应使用本技能。

ClawHub Agent Skills author: Morikawa v1.2.1 MIT-0 20 files body ≈ 1 975 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

国内电商全链路运营专家技能，覆盖淘宝、天猫、京东、拼多多、抖音电商、小红书、视频号、Temu八大平台。提供选品评分、定价与利润测算（含达人佣金）、广告投放ROI测算、店铺转化漏斗诊断、广告法违禁词合规检查、商品标题生成、备货与资金占用测算七个可计算工具，以及一个实时数据桥接器(live.py)——先用…

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

ProcedureSecuritytype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
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: 19. 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 "repository"
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "agent_created"

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 (web, python) that frontmatter does not declare
  • 100Steps. 60 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1975 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
  • +2Single-language instructions
  • +3Description length 361: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 60 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +3All 9 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: suspicious
The skill matches its ecommerce-operations purpose, but its live-data helper can place untrusted JSON values into shell commands that users or agents are told to execute.
LLM: suspicious (high) · 7 Sept 2026