processing-data
Processes CSV files and pandas DataFrames. Use when working with CSV files, tabular data, spreadsheets, or when the user asks to query, analyze, or manipulate structured data.
$ 安裝
git clone https://github.com/binome-dev/humcp /tmp/humcp && cp -r /tmp/humcp/src/tools/data ~/.claude/skills/humcp// tip: Run this command in your terminal to install the skill
SKILL.md
name: processing-data description: Processes CSV files and pandas DataFrames. Use when working with CSV files, tabular data, spreadsheets, or when the user asks to query, analyze, or manipulate structured data.
Data Processing Tools
Tools for working with CSV files and pandas DataFrames.
CSV Operations
List available CSV files
result = await list_csv_files()
# Returns: {"success": True, "data": ["file1", "file2"], "count": 2}
Read CSV content
result = await read_csv_file("mydata", row_limit=100)
# Returns rows as list of dicts
Query with SQL (DuckDB)
result = await query_csv_file("mydata", "SELECT * FROM mydata WHERE value > 10")
Security: Only SELECT queries allowed. INSERT, UPDATE, DELETE rejected.
Add/remove CSV files
await add_csv_file("/path/to/file.csv")
await remove_csv_file("filename")
Pandas Operations
Create DataFrame
# From CSV
result = await create_pandas_dataframe(
dataframe_name="sales",
create_using_function="read_csv",
function_parameters={"filepath_or_buffer": "data.csv"}
)
# From dict
result = await create_pandas_dataframe(
dataframe_name="mydf",
create_using_function="DataFrame",
function_parameters={"data": {"col1": [1, 2], "col2": [3, 4]}}
)
Allowed functions: DataFrame, read_csv, read_json, read_excel, read_parquet, read_feather, read_orc, read_html, read_xml, read_table, read_sql.
Run operations
# Get first rows
result = await run_dataframe_operation("sales", "head", {"n": 5})
# Filter data
result = await run_dataframe_operation("sales", "query", {"expr": "amount > 100"})
# Get statistics
result = await run_dataframe_operation("sales", "describe", {})
Allowed operations: head, tail, describe, query, filter, groupby, sort_values, mean, sum, count, and 100+ more safe operations.
Export DataFrame
result = await export_dataframe(
dataframe_name="sales",
export_function="to_csv",
export_parameters={"path_or_buf": "output.csv", "index": False}
)
Manage DataFrames
await list_dataframes() # List all in memory
await get_dataframe_info("sales") # Get details
await delete_dataframe("sales") # Remove from memory
Security Notes
- CSV queries: Only SELECT statements allowed
- Pandas: Operations restricted to allowlist of safe methods
- No arbitrary code execution via getattr
