Quantitative Analysis
Profile CSVs and compute transparent numeric summaries.
Skill metadata
| Source | Bundled (installed by default) |
| Path | skills/research/quantitative-analysis |
| Version | 1.0.0 |
| Author | VibeOS |
| License | MIT |
| Platforms | linux, macos, windows |
| Tags | research, analysis, csv, statistics, execute-code |
| Related skills | comparative-analysis, professional-research, longform-synthesis |
Reference: full SKILL.md
信息
The following is the complete skill definition that VibeOS loads when this skill is triggered. This is what the agent sees as instructions when the skill is active.
Quantitative Analysis Skill
Turn tabular data into clear numeric findings with reproducible steps.
Prefer execute_code (pandas if available) or the helper scripts here.
When to Use
- User provides CSV/TSV/XLSX or asks for stats, trends, cohorts, sensitivity.
- Need descriptive stats before a narrative conclusion.
Prerequisites
- Data file path known (or downloaded via tools).
execute_codeand/orterminalavailable.- Do not invent rows; if a column is missing, say so.
How to Run
- Profile the file (shape, dtypes, nulls, sample rows).
- Clean only with explicit rules (document drops/filters).
- Compute the metrics the question needs.
- Report with formulas, units, and caveats (sample size, outliers).
- Optional: write a small chart/table file via
execute_code.
Quick profile (stdlib):
python3 scripts/profile_csv.py path/to/data.csv
Output template
# Quantitative brief: <question>
## Dataset
- Path / URL:
- Rows × cols (after filters):
- Filters applied:
## Key metrics
| Metric | Value | Method |
|--------|-------|--------|
## Findings
1. …
2. …
## Sensitivity / caveats
- Missingness, outliers, selection bias
## Reproduce
Short `execute_code` or CLI snippet
Pitfalls
- Correlation ≠ causation — label associations clearly.
- Percentages need denominators.
- Don’t silent-drop nulls without stating count removed.
- Currency/timezone units must stay consistent.
Verification
- Row counts before/after filters stated.
- Each metric has a method note.
- Reproduce snippet works on the same file.