| name | csv-analysis |
| description | Analyze CSV files and generate comprehensive statistical reports with data profiling and quality checks |
| tools | ["powershell","view","create"] |
Instructions
When asked to analyze a CSV file, follow this workflow:
Step 1: Read and Profile
- Read the first 50 lines of the CSV
- Identify the delimiter (comma, tab, semicolon, pipe)
- Count total rows and columns
- Infer column data types (string, integer, float, date, boolean)
Step 2: Compute Statistics
Run analysis to compute per-column statistics:
- Count, nulls, unique values
- Min, max, mean, median, standard deviation for numeric columns
- Most frequent values for categorical columns
Step 3: Quality Assessment
Check for:
- Missing or null values (empty strings, "NA", "null", "N/A")
- Duplicate rows
- Inconsistent formatting (mixed date formats, case inconsistency)
- Potential outliers (values beyond 3 standard deviations)
Step 4: Generate Report
Create a markdown report with:
- Overview: File name, row count, column count
- Schema table: Column name, type, non-null count, unique count
- Statistics table: Min, max, mean, median, std dev for numeric columns
- Quality issues: List of findings with severity (info/warning/error)
- Key findings: Top 3-5 insights from the data
Output Format
The report should be a well-formatted markdown document suitable for inclusion in project documentation. Use tables for structured data and bullet points for findings.
Error Handling
- If the file is not valid CSV, report the issue and suggest the correct format
- If the file is too large (>100MB), sample the first 10,000 rows and note the sampling
- If encoding errors occur, try UTF-8, Latin-1, and CP1252 in order
