BC multi-research-free
多视角投研分析-基本面/技术面/新闻/风险辩论。针对A股领域的专业AI辅助工具，\n，去除原始风险代码，增强安全性和稳定性，\n补充完整的错误处理与边界情况，增加多场景使用示例。\n\。Use when 用户需要多视角投研分析相关功能时使用。不适用于超出本技能能力范围的复杂需求。适用于独立开发者、企业团队和自动化工作流场景。 功能涵盖: multi, research。
多视角投研分析-基本面/技术面/新闻/风险辩论。针对A股领域的专业AI辅助工具，\n，去除原始风险代码，增强安全性和稳定性，\n补充完整的错误处理与边界情况，增加多场景使用示例。\n\。Use when…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Invalid escape sequence \。 at line 6, column 106: …增强安全性和稳定性，\n补充完整的错误处理与边界情况，增加多场景使用示例。\n\。Use when 用户需要多视角投研分析相关功能时使用。不适用于超出本技能… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "summary" - note
frontmatter-keyunknown frontmatter key "tools"
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. Tools declared in frontmatter
- 100Steps. 89 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2075 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 186: enough signal without eating the budget
- +4Structure: 47 headings
- +3Step-by-step instructions: 89 items
- +4Has examples (7 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.