BD cue-cross-border-regulation
跨境法规调研 — 企业出海要合规、涉外诉讼要查明外国法、跨境投资要尽调、学术研究要对比中外规定，最怕境外法规「查不到、看不懂、判不准」：产品准入、GDPR 数据合规、出口管制、外商投资审查、跨境税务与转让定价、海外用工与签证，条款散落各国官方公报，英文原文难啃、适用边界难判。它直连 EUR-Lex、GovInfo、新加坡 Statutes 等官方权威数据库，定向检索目标司法辖区法规原文与核心条款，提炼立法背景与适用边界，关键条款附中文摘要，每个结论带官方出处、可逐条回查——出海合规、跨境诉讼、比较法研究都有据可依。 Triggers: 跨境法规、境外法规、外国法律、海外法规调研、欧盟法规、美国法律、GDPR、DMA、SEC规则、CFIUS、跨境合规、cross-border regulation、foreign law
跨境法规调研 — 企业出海要合规、涉外诉讼要查明外国法、跨境投资要尽调、学术研究要对比中外规定，最怕境外法规「查不到、看不懂、判不准」：产品准入、GDPR 数据合规、出口管制、外商投资审查、跨境税务与转让定价、海外用工与签证，条款散落各国官方公报，英文原文难啃、适用边界难判。它直连…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
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medium Exfiltration
net-credential-useSKILL.md:161Credential used in a network call (verify the destination is the intended service)echo "=== 2/3 Cue 服务 ===" && curl -sS --max-time 10 "https://cuecue.cn/api/health" -H "Authorization: Bearer $CUE_KEY"
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medium Exfiltration
net-credential-useSKILL.md:162Credential used in a network call (verify the destination is the intended service)echo "=== 3/3 搭子 ===" && curl -sS --max-time 10 "https://cuecue.cn/api/playbook" -H "Authorization: Bearer $CUE_KEY" | python3 -c "import sys,json;scenes=json.load(sys.stdin).get('data',{}).get('scene
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName"
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. 11 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1441 tokens
- 100Running it twice. No mutating operations
- low 14 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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +3Description length 364: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 11 items
- +4Has examples (7 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.