SKILLEMALL.ai

AC food-drug-cosmetics-ad-guard

食药化妆品广告合规护栏。在药品 / 医疗器械 / 保健食品 / 特殊医学用途配方食品 / 化妆品 的广告文案、产品详情、直播话术、对外宣传发布前,实时拦截功效断言保证、治愈率有效率、疾病治疗宣称、处方药违规发布、医疗作用暗示、绝对化用语等 6 类高频违法违规表述,按风险分级给出整改建议。纯本地运行,零网络、零动态执行。

ClawHub Agent Skills author: Wei Wu v1.0.0 MIT-0 9 files body ≈ 734 tokens Open the sourceclawhub.ai analyzed 3 d ago

食药化妆品广告合规护栏。在药品 / 医疗器械 / 保健食品 / 特殊医学用途配方食品 / 化妆品 的广告文案、产品详情、直播话术、对外宣传发布前,实时拦截功效断言保证、治愈率有效率、疾病治疗宣称、处方药违规发布、医疗作用暗示、绝对化用语等 6 类高频违法违规表述,按风险分级给出整改建议。纯本地运行,零网络、零动态执行。

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
C
53/100
Has gaps
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: 9. 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 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 21 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 734 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 160: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (2 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: clean
This skill is a local compliance keyword checker for Chinese food, drug, medical device, health food, and cosmetics advertising text, with no evidence of network access, persistence, credential use, or system changes.
LLM: benign (high) · VirusTotal: · 9 Aug 2026