OneResearchClaw: Skill for Cursor

Table Grounding

Convert a table file into a structured table-grounding bundle.

This skill is for table grounding, not a polished final report. It should produce a stable intermediate bundle that is easy for downstream skills and agents to use.

When to Use

Use this skill when:

• the input is a .xlsx or .csv file
• the file mainly contains tabular data
• you need a structured grounding note before downstream follow-up work
• you want schema, preview rows, summary statistics, and simple charts before writing conclusions

Do not use this skill when:

• the input is a PDF, DOCX, Markdown, or plain text document
• the goal is a polished final report
• the input is not primarily tabular

Input

A single table file:

• .xlsx
• .csv

For .xlsx, the default behavior is to use the first sheet. If a specific sheet is provided, use that sheet instead. Do not silently merge multiple sheets in the first version.

The table may contain:

• numeric columns
• categorical columns
• date/time columns
• missing values
• duplicated rows
• messy column names
• mixed types
• derived or computed columns

Output Bundle

Write outputs under:

data/grounded_notes/<type>-<table_id>/

If a specific xlsx sheet is selected, the bundle directory may include a sheet suffix.

Examples:

• data/grounded_notes/xlsx-sales_q1/
• data/grounded_notes/xlsx-sales_q1-sheet-Summary/
• data/grounded_notes/csv-benchmark_results/

The bundle should contain:

<bundle_dir>/
├─ extracted.md
├─ extracted_meta.json
├─ schema.json
├─ summary_stats.json
├─ asset_index.json
└─ assets/
   ├─ previews/
   │  ├─ head.csv
   │  ├─ sampled_rows.csv
   │  └─ column_summary.md
   └─ charts/
      ├─ chart_001.png
      ├─ chart_002.png
      └─ ...

Important:

• The script stage must not generate a placeholder grounded.md.
• The agent must read the bundle and then write a real grounded.md.

Required Workflow

When using this skill, you must follow this workflow: