BF portfolio-diagnosis (Public)
持仓诊断技能(Tushare驱动版)——专为A股投资者设计。当用户说"帮我诊断持仓"、"看看我的股票组合"、"仓位合理吗"、"持仓风险大吗"、"我的组合夏普比率多少"时触发。使用Tushare SDK获取实时行情和历史数据，进行包含波动率、Beta、夏普比率、最大回撤在内的量化风险诊断，并生成专业诊断报告,包含：英雄区 + 综合评分环形图;持仓概览关键指标卡片;个股明细表格（含仓位进度条）;四大量化指标卡片（波动率/Beta/夏普/回撤）;四张交互式 Chart.js 图表（雷达图/饼图/柱状图/盈亏对比）;六维诊断卡片、风险提示、优化建议;得分明细条形图。
As a process F 34/100 · Will not run — weak spots: result and completion, when it triggers, inputs and preconditions
The same skill appears in 1 more place: ClawHub
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 · 0
✓ No critical or high findings
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "input_format" - note
frontmatter-keyunknown frontmatter key "trigger"
Process rating: all ten parameters 34/100
- 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
- 40Consistency. Frontmatter name (portfolio-diagnosis (Public)) differs from the folder (portfolio-diagnosis)
- 50Steps. 2 steps
- 60Tools and files. Uses tools (python, node) that frontmatter does not declare
- 100Execution cost. Instruction body is 127 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
- +4Description does not say when NOT to use the skill (false activations)
- +4Structure: 1 headings, hard to scan
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 282: enough signal without eating the budget
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.