AB data-analyst
Enterprise-grade data analysis assistant. Clean, analyze, and visualize data automatically. **Triggers when user mentions:** - Data cleaning: "数据清洗", "整理数据", "清理数据", "数据预处理" - Data analysis: "分析数据", "数据分析", "数据报表", "生成报告" - Visualization: "画图", "图表", "可视化", "生成图表" - Excel/CSV: "处理Excel", "分析CSV", "读取表格" - Insights: "数据洞察", "发现规律", "趋势分析" Supports Excel (.xlsx), CSV, JSON formats. Generates reports, charts, and insights.
As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, consistency, running it twice
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: 19. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 65/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (data-analyst) differs from the folder (smart-data-insights)
- 50Failures and branches. 0 branches, has a failure section
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 24 steps
- 100Execution cost. Instruction body is 1024 tokens
- low 11 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)
- -212 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 425: enough signal without eating the budget
- +4Structure: 23 headings
- +3Step-by-step instructions: 24 items
- +3Output format is stated explicitly
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.