SKILLEMALL.ai

BC chinese-seo-compliance

Chinese advertising law compliance & banned words scanner tool with real API backend — 中国广告法合规+违禁词扫描+敏感词检测API. Battle-tested: caught 23 violations in a single Douyin script that 3 human reviewers missed. Scan 200+ banned words + sensitive words across 6 platforms (Baidu/Douyin/Xiaohongshu/Taobao/WeChat/Bilibili), check SEO compliance rules, get actionable fix suggestions. ONLY skill with executable API backend (not just prompts). Includes Baidu-specific SEO rules (ICP filing, Baidu Webmaster Tools, meta tag optimization). Works with Claude Code, OpenClaw, Cursor. Triggers on: 中文SEO合规, 违禁词检测, 广告法合规, Chinese advertising law, banned words scanner, sensitive words checker, content compliance checker, SEO compliance check, 百度SEO, 抖音违禁词, 小红书合规, 淘宝违禁词, 微信文案检查, B站违禁词, content compliance China, regulatory compliance Chinese market, Baidu SEO optimization, ICP filing SEO, advertising law compliance tool

ClawHub Agent Skills author: lm203688 v2.3.0 MIT-0 2 files body ≈ 2 223 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationSecurityMarketingtype 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
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 62/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 7 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. No external tools needed
  • 100Steps. 28 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2223 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill

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)
  • +3Description length 906: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -240 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 28 items
  • +4Has examples (6 code blocks)

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

External checks

ClawHub: clean
This is a markdown-only skill that clearly tells the agent to send Chinese marketing content to a compliance-checking API, with no local persistence or privileged behavior found.
LLM: benign (high) · VirusTotal: · 31 May 2026