s3-explore

name	s3-explore
description	Explore and query data on S3, Cloudflare R2, GCS, MinIO, or any S3-compatible storage. Use when the user mentions an s3://, r2://, gs://, or gcs:// URL, asks "what's in this bucket", wants to list remote files, preview remote Parquet/CSV/JSON, or query data on object storage without downloading it. Also triggers when the user wants to know the size, schema, or row count of remote datasets.
argument-hint	<s3-url> [question about the data]
allowed-tools	Bash

You are helping the user explore data on remote object storage using DuckDB.

URL: $0 Question: ${1:-list and describe what's there}

Step 1 — Detect provider and set up credentials

Based on the URL or user context, prepend the appropriate secret configuration:

Provider	URL patterns	Secret setup
AWS S3	s3://	CREATE SECRET (TYPE S3, PROVIDER credential_chain);
Cloudflare R2	r2://, s3:// with R2 endpoint	CREATE SECRET (TYPE R2, PROVIDER credential_chain);
GCS	gs://, gcs://	CREATE SECRET (TYPE GCS, PROVIDER credential_chain);
MinIO / custom	s3:// with custom endpoint	CREATE SECRET (TYPE S3, KEY_ID '...', SECRET '...', ENDPOINT '...', USE_SSL true);

For R2, if the user provides an account ID, the endpoint is <account_id>.r2.cloudflarestorage.com. R2 URLs like r2://bucket/path should be rewritten to s3://bucket/path with the R2 secret.

For public buckets (e.g., Overture Maps, AWS open data), no secret is needed — skip this step.

Always prepend:

LOAD httpfs;

Step 2 — Determine what the URL points to

If the URL looks like a directory or bucket (no file extension, or ends with /), list its contents with sizes:

duckdb -c "
LOAD httpfs;
<SECRET_SETUP>
SELECT filename, (size / 1024 / 1024)::DECIMAL(10,1) AS size_mb, last_modified
FROM read_blob('<URL>/*')
ORDER BY filename
LIMIT 50;
"

Note: only select filename, size, last_modified — never select content, which would download the actual files.

If the URL points to a specific file or glob pattern (has a file extension or contains *), preview it:

duckdb -c "
LOAD httpfs;
<SECRET_SETUP>
DESCRIBE FROM '<URL>';
SELECT count(*) AS row_count FROM '<URL>';
FROM '<URL>' LIMIT 20;
"

For Parquet files, get row counts and sizes from metadata (no data download):

duckdb -c "
LOAD httpfs;
<SECRET_SETUP>
SELECT file_name,
       sum(row_group_num_rows) AS total_rows,
       (sum(row_group_compressed_bytes) / 1024 / 1024)::DECIMAL(10,1) AS compressed_mb
FROM parquet_metadata('<URL>')
GROUP BY file_name;
"

Step 3 — Answer the question

Using the listing, schema, or sample data, answer:

${1:-list and describe what's there}

If the user asks an analytical question (e.g., "how many rows match X"), write and run the appropriate SQL query. DuckDB pushes predicates down into Parquet on S3, so filtering is efficient even on large remote datasets.

Error handling

• duckdb: command not found → delegate to /duckdb-skills:install-duckdb
• Access denied / 403 → suggest the user check credentials: aws configure, environment variables, or provide explicit key/secret
• Bucket not found / 404 → check the URL and region
• Timeout on large listing → suggest narrowing the glob pattern or adding a prefix