Extract tables from AI output
Large language models love to answer in markdown tables — comparisons, pricing grids, feature matrices. But you usually need that data somewhere else: a spreadsheet, a database seed, a config file. Copy-pasting a markdown table into Excel gives you one mangled cell. This tool finds every table in the response and converts it to CSV, TSV, or JSON you can actually use.
How it works
The extractor scans the text line by line looking for table blocks: a header row,
a dash separator row, and one or more data rows, all delimited by |. Edge pipes
are optional and whitespace is trimmed, so even sloppy LLM formatting parses:
| Model | Context | -> Model,Context
|-------|---------| GPT-4o,128k
| GPT-4o | 128k | Claude,200k
| Claude | 200k |
Each detected table is parsed into rows of cells, then serialised into your chosen format. CSV escaping follows RFC 4180 so commas and quotes inside cells survive.
Tips and notes
If a table is not detected, check that the separator line (|---|---|) is present —
that dashed row is what distinguishes a real table from accidental pipe characters.
For JSON, keep your header row meaningful since it becomes the object keys. When an
LLM emits several comparison tables in one answer, each is extracted separately so
you can take only the one you need without hand-editing.