duckdb/duckdb-skills

s3-explore

Explore and query data on S3, Cloudflare R2, GCS, MinIO, or any S3-compatible storage.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/duckdb/duckdb-skills --skill s3-explore

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

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:

ProviderURL patternsSecret setup
AWS S3s3://CREATE SECRET (TYPE S3, PROVIDER credential_chain);
Cloudflare R2r2://, s3:// with R2 endpointCREATE SECRET (TYPE R2, PROVIDER credential_chain);
GCSgs://, gcs://CREATE SECRET (TYPE GCS, PROVIDER credential_chain);
MinIO / customs3:// with custom endpointCREATE 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:

sql
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:

bash
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:

bash
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):

bash
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

Verwandte Aufgaben

aus demselben Repository

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