read-file
Read any data file (CSV, JSON, Parquet, Avro, Excel, spatial, SQLite) or remote URL (S3, HTTPS). Use when user references a data file, asks "what's in this file", or wants to preview/profile a dataset. Not for source code.
What this skill does
You are helping the user read and analyze a data file using DuckDB.
Filename given: `$0`
Question: `${1:-describe the data}`
## Step 1 — Read it
`RESOLVED_PATH` is `$0`. If the user gave a bare filename (no `/`), resolve it to a full path with `find` first.
Run a single DuckDB command that defines the `read_any` macro inline and reads the file.
For **remote files**, prepend the necessary LOAD/SECRET before the macro:
| Protocol | Prepend |
|---|---|
| `https://` / `http://` | `LOAD httpfs;` |
| `s3://` | `LOAD httpfs; CREATE SECRET (TYPE S3, PROVIDER credential_chain);` |
| `gs://` / `gcs://` | `LOAD httpfs; CREATE SECRET (TYPE GCS, PROVIDER credential_chain);` |
| `az://` / `azure://` / `abfss://` | `LOAD httpfs; LOAD azure; CREATE SECRET (TYPE AZURE, PROVIDER credential_chain);` |
For **local files**, no prefix needed.
```bash
duckdb -csv -c "
CREATE OR REPLACE MACRO read_any(file_name) AS TABLE
WITH json_case AS (FROM read_json_auto(file_name))
, csv_case AS (FROM read_csv(file_name))
, parquet_case AS (FROM read_parquet(file_name))
, avro_case AS (FROM read_avro(file_name))
, blob_case AS (FROM read_blob(file_name))
, spatial_case AS (FROM st_read(file_name))
, excel_case AS (FROM read_xlsx(file_name))
, sqlite_case AS (FROM sqlite_scan(file_name, (SELECT name FROM sqlite_master(file_name) LIMIT 1)))
, ipynb_case AS (
WITH nb AS (FROM read_json_auto(file_name))
SELECT cell_idx, cell.cell_type,
array_to_string(cell.source, '') AS source,
cell.execution_count
FROM nb, UNNEST(cells) WITH ORDINALITY AS t(cell, cell_idx)
ORDER BY cell_idx
)
FROM query_table(
CASE
WHEN file_name ILIKE '%.json' OR file_name ILIKE '%.jsonl' OR file_name ILIKE '%.ndjson' OR file_name ILIKE '%.geojson' OR file_name ILIKE '%.geojsonl' OR file_name ILIKE '%.har' THEN 'json_case'
WHEN file_name ILIKE '%.csv' OR file_name ILIKE '%.tsv' OR file_name ILIKE '%.tab' OR file_name ILIKE '%.txt' THEN 'csv_case'
WHEN file_name ILIKE '%.parquet' OR file_name ILIKE '%.pq' THEN 'parquet_case'
WHEN file_name ILIKE '%.avro' THEN 'avro_case'
WHEN file_name ILIKE '%.xlsx' OR file_name ILIKE '%.xls' THEN 'excel_case'
WHEN file_name ILIKE '%.shp' OR file_name ILIKE '%.gpkg' OR file_name ILIKE '%.fgb' OR file_name ILIKE '%.kml' THEN 'spatial_case'
WHEN file_name ILIKE '%.ipynb' THEN 'ipynb_case'
WHEN file_name ILIKE '%.db' OR file_name ILIKE '%.sqlite' OR file_name ILIKE '%.sqlite3' THEN 'sqlite_case'
ELSE 'blob_case'
END
);
DESCRIBE FROM read_any('RESOLVED_PATH');
SELECT count(*) AS row_count FROM read_any('RESOLVED_PATH');
FROM read_any('RESOLVED_PATH') LIMIT 20;
"
```
**If this fails:**
- **`duckdb: command not found`** → invoke `/duckdb-skills:install-duckdb` and retry.
- **Missing extension** (e.g. spatial files, xlsx, sqlite) → retry with `INSTALL spatial; LOAD spatial;` or `INSTALL sqlite_scanner; LOAD sqlite_scanner;` prepended before the macro.
- **Wrong reader / parse error** → use the correct `read_*` function directly instead of `read_any`.
## Step 2 — Answer
Using the schema, row count, and sample rows, answer:
`${1:-describe the data: summarize column types, row count, and any notable patterns.}`
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