Office DuckDB Read File
This skill is absorbed from the DuckDB official read-file workflow and adapted to ContextGo office analysis.
What it is for
Before writing queries, profile the file properly:
- what columns exist
- what row count looks like
- what the sample values suggest
- which reader or extension is needed
Use when
- The user asks what is inside a data file.
- You need to inspect a CSV, Parquet, JSON, Excel, SQLite, or similar file before deeper analysis.
- You want a file-aware profile before moving to SQL-style querying.
Do not use when
- The data model is already understood and the user is clearly asking for a query result.
- The task is centered on office documents rather than data files.
Workflow
Step 1: Resolve the file
Make sure the path or URL is real and identify:
- local or remote
- likely file type
- whether an extension may be needed
Step 2: Read with the right strategy
Use DuckDB's file readers or a read_any style macro mindset:
- CSV / TSV
- JSON
- Parquet
- Excel
- SQLite
- remote object storage when needed
If the generic path fails, switch to the exact reader instead of guessing blindly.
Step 3: Profile the file
Always try to produce:
- schema
- row count
- sample rows
This is the minimum useful profile.
Step 4: Turn the profile into next questions
After profiling, say:
- what the file most likely represents
- what quality issues are visible
- which query should come next
Output format
Return:
1. File profile
- file type
- likely content
- schema
2. Volume and sample
- row count
- sample notes
3. Data quality watchpoints
- missing values
- odd types
- suspicious fields
4. Recommended next query
- one or two SQL-style follow-ups
Use together with
office-duckdb-queryoffice-duckdb-installoffice-spreadsheet-analysiswhen the file is an Excel workbook acting as a dataset