AC guanshi-deep-insight
深度洞察引擎 — 对任何分析结论执行穿透式深度审查，输出带有因果链、反事实场景和张力暴露的洞察报告。不与领域知识耦合，只负责分析方法论。Use when 需要深化分析结论、穿透表层判断、暴露战略建议的可执行性风险。不适用于领域数据查询、简单事实确认。
深度洞察引擎 — 对任何分析结论执行穿透式深度审查，输出带有因果链、反事实场景和张力暴露的洞察报告。不与领域知识耦合，只负责分析方法论。Use when 需要深化分析结论、穿透表层判断、暴露战略建议的可执行性风险。不适用于领域数据查询、简单事实确认。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
Proceduretype and topics are labelled automatically from the skill text
How to improve
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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Risky intent
intent-offensive-securitySKILL.md:75Offensive-security / dual-use content (legitimate for authorised testing; review intended use)### 第二步：红队审查（Red Teaming）
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "guanshi_expert"
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. 22 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 604 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 125: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (7 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.
External checks
ClawHub: clean
This is a disclosed Chinese-language analysis methodology skill with no code, dependencies, persistence, or data access behavior.
LLM: benign (high) · VirusTotal: · 7 Jun 2026