Your agent can't reliably reshape large CSV, JSON, or XLSX by hand; this converts and filters them with a structured spec.
Convert tabular data between CSV, JSON, and XLSX, and reshape it (select, filter, sort, limit) with a structured spec. 0.5 credits per MB of input.
Select columns, filter and sort rows, and limit, then convert format.
Target format.
Source format.
Keep at most this many rows.
Sheet name for xlsx input.
Columns to keep, in this order.
Row filters, AND-combined.
Sort keys, applied in order.
Pre-signed GET URL of the input file.
Download URL TTL in seconds.
Filename for the output. Defaults to reshaped.<to>.
curl -X POST "https://skill.askfaro.com/skills/tabular/run" \
-H "Authorization: Bearer faro_<your_key>" \
-H "Content-Type: application/json" \
-d '{
"intent": {
"prompt": "From this CSV keep only name and revenue where revenue is over 1000, sorted descending"
}
}'askfaro describe tabular/reshape
Install pip install askfaro-cli, then askfaro auth login.
Target format.
Source format.
Sheet name for xlsx input (default first sheet).
Pre-signed GET URL of the input file.
Download URL TTL in seconds.
Filename for the output. Defaults to output.<to>.
curl -X POST "https://skill.askfaro.com/skills/tabular/run" \
-H "Authorization: Bearer faro_<your_key>" \
-H "Content-Type: application/json" \
-d '{
"intent": {
"prompt": "Convert this CSV to XLSX"
}
}'askfaro describe tabular/convert
Install pip install askfaro-cli, then askfaro auth login.
Interconvert CSV, JSON, and XLSX, and apply a structured reshape (column selection, row filters, sorting, and limit) with no arbitrary code execution.
POST /uploads/presign on faro-api, PUT your file, pass the get_url as input_url.from and to formats; download the result from download_url.0.5 credits per MB of input.
Input up to 50 MB and 1,000,000 rows. Reshape ops are a fixed vocabulary (eq/ne/gt/lt/ge/le/contains/in/notnull/isnull), there is no query/eval string.